CN110276479A - The cruising phase fuel consumption prediction technique of Aircraft Quality variation - Google Patents
The cruising phase fuel consumption prediction technique of Aircraft Quality variation Download PDFInfo
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Abstract
The present invention discloses a kind of cruising phase fuel consumption prediction technique of flight reappearance variation, includes the following steps: step 1, considers the influence of mass change and crosswind, constructs cruising phase fuel consumption model；Step 2, the model constructed for step 1, establishes objective function and constraint condition；Step 3, the optimal solution for solving objective function obtains optimal fuel mileage and corresponding best cruise altitude and Maximum Endurance Mach number under each quality.Such prediction technique can establish the cruise oil consumption prediction model based on aircraft mass change, and by the model, calculated by optimization, determine best cruise altitude corresponding to the maximum fuel mileage of different aircraft quality and best cruising speed.
Description
Technical field
The present invention relates to a kind of cruising phase fuel consumption prediction techniques of Aircraft Quality variation.
Background technique
With the fast development of air transportation, it is predicted that at next 15 years, air traffic amount is by double [1].And fuel oil
The rise of price and the limitation of environmental policy determine that aircraft saving fuel oil consumption problem becomes the manager of blank pipe and dispatch
With the hot issue of researcher's concern.According to International Air Transport Association (International Air Transport
Association, IATA) report [2], the fuel cost of aircraft has accounted for 35% of airline operation cost or more, on
First in airline's main business cost is risen to, the benefit space of airline has been greatly reduced, airline faces
Huge survival pressure.IATA [2] and International Civil Aviation Organization [3] are proposed the long-term goal for improving flight fuel efficiency.Mesh
Before, the sight for reducing fuel consumption is concentrated on accurate prediction aircraft fuel oil loading capacity one after another by airline, avoids " rusting oil "
The phenomenon that, to reduce course line oil consumption, improve fuel oil service efficiency.Large-scale airline carriers of passengers is in medium and long distance voyage, for length
The flight of voyage, the large percentage of entire whole flight oil consumption shared by cruising flight phase fuel consumption.Therefore, it establishes quasi-
True cruising flight phase fuel consumption prediction model realizes accurate control fuel oil loading capacity, for improving airline's operation
Benefit reduces fuel emission and is of great significance.
Cruising phase influences in the factors of fuel consumption Accurate Prediction, and aeroplane performance and flight crosswind are two important
Factor.In terms of crosswind is for the influence of fuel consumption: Vazquez and Rivas [4] has studied under the uncertainty of wind,
Stochastic variable is added by nonlinear method, determines that cruising phase fuel oil quality changes, and compare with monte carlo method,
Show that this method has great advantage on calculating the time, but the probability density function of wind used in this research is common
It is uniformly distributed and β is distributed, rather than come from true wind data, leading to calculated result, there are errors.Franco and Rivas[5]
It analyzes in the case where there is high wind in the least cost problem of constant altitude cruise, including reaches tardiness cost, it is contemplated that one
As instability problem and there is no any restrictions to cruising altitude comprising Aircraft Quality in the influence of variation.This is researched and analysed
Reach the optimum trajectory of least cost, the i.e. functional relation of speed and Aircraft Quality, but is not directed to crosswind this factor pair
The influence of fuel cost is analyzed.Assaad and Bil [6] is subtracted by considering the influence optimization transport air flow of crosswind
Few fuel consumption.But this research only considered influence with the wind, has ignored against the wind, is not suitable for practical application.Jensen
And John Hansman [7] etc. analyzes 200000 history flight records, calculates actual wind speed experienced of flying
And temperature, generate various optimum height profiles and be compared with flight baseline, propose by optimization cruising altitude and speed come
Fixed lateral route is given, so that reducing the economy of fuel consumption and environment influences, but not in view of aircraft quality
Change the influence to fuel consumption.Svensson et al [8] re-optimization and compare two kinds of equivalent medium-haul aircraft, Yi Zhongmei
Oil fuel and a kind of LH2 fuel, reduce cruising altitude from the angle of environment.By reducing cruising altitude, can reduce to complete
The contribution that ball warms, while fuel consumption and discharge are reduced, but influence of the cruising altitude to oil consumption is only considered in studying, ignore
The influence of flight Mach number.Franco et al [9] etc. is based on probability conversion method, develops probability trajectories fallout predictor, passes through
Input the probability density function of the average ground speed of cruise section, the probability density letter of exportable flight time and fuel consumption
Number solves the uncertain aircraft trace forecasting problem influenced of wind-engaging, but Aircraft Quality becomes during not considering cruise
Change the influence to flight time and fuel consumption.
In terms of performance factor is for fuel oil influence factor: Vazquez and Rivas [10] is analyzed to patrol with given
Under the conditions of fuel load of navigating and given two kinds of cruising range, initial mass distribution meets uniform gamma type, cruising flight
The middle probabilistic fuel consumption of initial mass.Schilling [11] using neural network lift and resistance, thrust and
Performance parameter is added in the relational model of fuel flow, avoids the manual operations of performance graph inquiry, improves calculating speed.
But the model does not account for airplane motion related data, can not directly calculate practical fuel consumption.Turguta et al[12]
Etc. the empirical equation for developing cruising phase fuel stream, can be used for preferably calculating fuel consumption, result of study characterizes three
The influence of Specifeca tion speeification, cruising altitude, quality and speed to fuel flow rate, but not in view of air pressure, temperature, crosswind etc.
Influence of the essential environmental factors to fuel consumption.Williams et al [13] has evaluated the height of up to 6000 nautical miles of long voyage
Degree limitation, the tradeoff between fuel consumption and journey time；The flying height 18,000 and 31 from different type of airplane is analyzed,
The variation of 000 foot of relevant fuel combustion and running time, it may be to mitigate aircraft industry pair that obtaining, which reduces aircraft cruising altitude,
The beneficial policy of climate change effect, but not in view of Aircraft Quality variation is to the shadow of fuel consumption and discharge in this research
It rings.
International Civil Aviation Organization (ICAO) [14], Federal Aviation management board (FAA) [15] and European aviation safety
Some government organization including (EUROCONTROL) [16] are organized, establish the calculating side of aircraft fuel oil consumption and discharge in succession
Method.Federal Aviation management board establishes AEDT software [15], for predicting the aircraft fuel oil consumption of all flights in the whole world
And discharge amount.European aviation safety tissue [16] calculates entire flight course each stage using aircraft performance database (BADA)
Fuel consumption and discharge amount, but shadow brought by performance degradation is not considered using the calculated oil consumption of BADA database
It rings.Air Passenger PEP performance software for calculation [17] oil consumption module, may be used as calculate flight plan fuel consumption, but due to
There is no real-time wind-warm syndrome data, real-time fuel consumption data can not be obtained and can not consider weather environment.
Chipset rapid data access logger (Quick Access Recorder) is more and more common by each airline
The calculating of dispatch department performance is used, and by extracting QAR operation data, fuel consumption model is predicted, as Trani [18] is based on
QAR data and performance database training neural network obtain fuel consumption, and this method selects performance data to require height, not
Consider height change, and the neural network structure convergence rate proposed is slower, and does not consider crosswind to the shadow of fuel consumption
It rings, does not meet actual motion environment.Transporter mission phase of the Baklacioglu [19] based on Genetic Algorithm Optimized Neural Network
Amount of fuel modeling, which establishes neural network model using true QAR flying quality, by the change of flying height and true airspeed
Change while incorporating in model, but does not consider meteorologic factor equally.Assaad et al. [20] is excellent by the influence for considering crosswind
Change transport air flow to reduce fuel consumption, but only considered influence with the wind, has ignored against the wind, be not suitable for actually answering
With, and do not calculate crosswind addition fuel consumption model.
In conclusion the oil consumption forecasting research of the process of aircraft cruise at this stage mostly not by performance parameter, crosswind and flies
Machine mass change comprehensively considers in oil consumption prediction model, and leading to prediction result, there is a certain error.
Bibliography involved in text is as follows:
[1]Airbus,Flying by numbers:global market forecast for 2015-2034,
2015.Available online:<https://espas.secure.europarl.europa.eu/orbis/
document/flying-numbers-global-market-forecast-2015-2034>.
[2]International Air Transport Association(IATA).Economic performance
of the airline industry:2015end-year report[R],2015.
[3]ICAO.Carbon emissions calculator methodology,8th version[R],2015
[4]R.Vazquez,D.Rivas,Analysis of the effect of uncertain average
winds on cruise fuel load[C],in:Proc.5th SESAR Innovation Days,2015
[5]Antonio Franco and Damián Rivas.Minimum-Cost Cruise at Constant
Altitude of Commercial Aircraft Including Wind Effects,JOURNAL OF GUIDANCE,
CONTROL,AND DYNAMICS,Vol.34,No.4,July–August 2011
[6]Z Assaad,C Bil,A Eberhard,M Moore.Reducing Fuel Burn through Air
Traffic Flow Optimisation Incorporating Wind Models[J].Procedia Engineering,
2015,99(1-2):1637-1641.
[7]Luke Jensen,R John Hansman,Joseph Venuti,and Tom Reynolds."
Commercial Airline Altitude Optimization Strategies for Reduced Cruise Fuel
Consumption",14th AIAA Aviation Technology,Integration,and Operations
Conference,AIAA AVIATION Forum,(AIAA 2014-3006)
[8]F.Svensson,A.Hasselrot,J.Moldanova,Reduced environmental impact by
lowered cruise altitude for liquid hydrogen-fuelled aircraft,
Aerosp.Sci.Technol.8(2004)307–320.
[9]Antonio Franco,DamiánRivas,Alfonso Valenzuela.Probabilistic
aircraft trajectory prediction in cruise flight considering ensemble wind
forecasts,Aerospace Science and Technology 82–83(2018)350–362
[10]R.Vazquez,D.Rivas,Propagation of initial mass uncertainty in
aircraft cruise flight,J.Guid.Control Dyn.36(2)(2013)415–429.
[11]Schilling,G.D.Modeling aircraft fuel consumption with a neural
network.Virginia Polytechnic Institute and State University,1997.
[12]Enis T.Turguta,Mustafa Cavcarb,Oznur Usanmazc,A.Ozan
Canarslanlarc,Tuncay Dogeroglud,Kadir Armutlue,Ozan D.Yay.Fuel flow analysis
for the cruise phase of commercial aircraft on domestic routes,Aerospace
Scienceand Technology,37(2014),1-9
[13]V.Williams,R.B.Noland,R.Toumi,Air transport cruise altitude
restrictions to minimizecon trail formation,Climate Policy 3(3)(2003)207–219.
[14]ICAO.Carbon emissions calculator methodology,8th version[R],2015.
[15]Ahearn,M,et al.Aviation Environmental Design Tool(AEDT)technical
manual,Version 2b[R],Service Pack 3,U.S.Department of Transportation John
A.Volpe National Transportation Systems Center,Report No.DOT-VNTSC-FAA-16-11,
2016
[16]Eurocontrol Experimental Centre.User manual for the base of
aircraft DATA(BADA)revision 3.9[R],EEC technical/Scientific Report No.11/03/
08-08,2011.
[17]Airbus,AIRBUS Performance Engineers’Programs for Microsoft
Windows fundamentals,2010.
[18]Trani A,Wingho F,Schilling G,et al.ANeural Network Model to
Estimate Aircraft Fuel Consumption[J].Aiaa Journal,2004,10:61-68.
[19]T Baklacioglu.Modeling the fuel flow-rate of transport aircraft
during flight phases using genetic algorithm-optimized neural networks[J]
.Aerospace Science and Technology,2016,49(3):52-62.
[20]Z Assaad,C Bil,AEberhard,M Moore.Reducing Fuel Burn through Air
Traffic Flow Optimisation Incorporating Wind Models.Procedia Engineering,
2015,99(1-2):1637-1641.
Summary of the invention
The purpose of the present invention is to provide a kind of cruising phase fuel consumption prediction technique of Aircraft Quality variation, can
The cruise oil consumption prediction model based on aircraft mass change is established, and by the model, is calculated by optimization, determines difference
Best cruise altitude corresponding to the maximum fuel mileage of aircraft quality and best cruising speed.
In order to achieve the above objectives, solution of the invention is:
A kind of cruising phase fuel consumption prediction technique of flight reappearance variation, includes the following steps:
Step 1, consider the influence of mass change and crosswind, construct cruising phase fuel consumption model；
Step 2, the model constructed for step 1, establishes objective function and constraint condition；
Step 3, the optimal solution for solving objective function obtains optimal fuel mileage under each quality and corresponding best
Cruising altitude and Maximum Endurance Mach number.
In above-mentioned steps 1, the cruising phase fuel consumption model of building is expressed as:
Wherein, Q is hour fuel consumption；N is engine number of units；Cf1,Cf2Respectively the first and second specific thrust fuel oil
Consumption coefficient；VTASFor flight true air speed；CD0,CD1Respectively the first, second resistance coefficient；The atmosphere that ρ is height above sea level when being H
Pressure；S is aircraft wing area；V is aircraft relative velocity；mi-1For (i-1)-th second Aircraft Quality；Fi-1It is (i-1)-th second
Fuel consumption；G is the acceleration of gravity of aircraft；CfcrFor the fuel oil correction factor that cruises.
In above-mentioned steps 2, the objective function of foundation is:
Wherein:
Constraint condition are as follows: 0.5≤M≤0.82
39t≤m≤77t
H=8100,8400,8900,9200,9500,9800,10100,10400,10700,11000,11300,
11600,11900 }
Decision variable are as follows: Hj, Mj
Wherein, Hj, MjRespectively indicate corresponding flying height and Mach number when Aircraft Quality is j.
In above-mentioned steps 3, solved using genetic algorithm, solve in accordance with the following steps corresponding each quality j ∈ [39,
77] optimal solution:
The first step, setting Population Size P, select probability G, crossover probability J, mutation probability B and maximum number of iterations M；
Second step encodes the chromosome for carrying information, i.e., to the flying height and Mach number point under each quality j
H is not encoded to itj, Mj；It is then based on coding and generates corresponding random number, be expressed as Random (Hj) and Random (Mj), wherein
Random(Hj) ∈ [8100,8400,8900,9200,9500,9800,10100,10400,10700,11000,11300,
11600,11900], Random (Mj) ∈ [0.50,0.82], it is divided into 0.01；
Corresponding random number is generated based on coding, according to the Population Size P of setting, generates P chromosome, wherein each dyeing
Gene in body is that random sequence generates；
Third step calculates fitness individual in population；
4th step chooses number of individuals according to select probability G；
The 4th selected individual of step is carried out cross exchanged gene, wherein each individual is intersected by the 5th step two-by-two
The probability of exchange depends on crossover probability J；
Step 6: carrying out genetic mutation according to mutation probability B using the variation method of exchange genic value, that is, randomly choosing
One chromosome reselects its corresponding gene；
7th step finally acquires the target function value under 39 to 77 tons of quality using the number of iterations as termination condition.
In above-mentioned third step, following fitness function is chosen:
F (x)=SRj,j∈[39,77]
Wherein, the expression formula of fuel mileage SR are as follows:
Wherein, VTASFor flight true air speed；Q is hour fuel consumption.
In above-mentioned 4th step, the method that selecting object uses random competition chooses one by roulette selection mechanism every time
To individual, the two individuals is then allowed to be at war with, according to front fitness function calculated result, so that the individual that fitness is high
It is selected, repeatedly, until be full (number of individuals in G × initial population) it is a until, then replicate again (individual in initial population
Number of individuals in number-G × initial population) the high individual of a fitness.
In above-mentioned 5th step, using common single-point type crossing operation, the i.e. random sequence in flying height and Mach number
In, exchange the gene of two parent chromosomes.
After adopting the above scheme, the method have the advantages that:
(1) for the less influence for considering mass change to fuel consumption in the research of cruising phase fuel consumption model, and
Cruising flight phase accounts for very big specific gravity in medium-long range segment, and set forth herein the cruising phase fuel consumption optimizations for considering mass change
Model, and in Optimized model be added crosswind influence；
(2) it is compared by research example data and the true fuel consumption data of QAR, accuracy is up to 91.7%, and excellent according to institute
The cruising phase fuel consumption model of change calculates maximum corresponding to different flight reappearances in entire cruising phase flight course
Voyage Mach number and best cruise altitude.
Detailed description of the invention
Fig. 1 is fuel consumption comparison diagram；
Fig. 2 is cruising flight Mach number, flying height and hour fuel consumption values 3-D image；
Fig. 3 is fuel mileage of 8100 meters of flying heights in different flight Mach number conditions；
Fig. 4 is fuel mileage of the different flying heights in different flight Mach number conditions；
Fig. 5 is cruising flight Mach number, flying height and fuel mileage 3-D image；
Fig. 6 is the optimal three-dimensional relationship figure of A320 economy；
Fig. 7 is two kinds of method for solving comparative result figures；
Fig. 8 is that the cruising phase Optimized model in the present invention solves flow chart.
Specific embodiment
Below with reference to attached drawing, technical solution of the present invention and beneficial effect are described in detail.
1. summarizing
For shadow of the variation to fuel consumption for not considering quality in BADA database in cruising phase fuel consumption model
It rings, is influenced this paper presents cruising phase by crosswind and aircraft weight changes lower fuel consumption prediction model.Meanwhile for
Toward not considering influence of the wind to fuel mileage by model-performance handbook, and do not consider Aircraft Quality at any time in the influence of variation,
We use above-mentioned fuel consumption prediction model, analyze different Mach number and different flying heights to fuel mileage (SR)
It influences, it is high to find ultimate run Mach number corresponding to different flight reappearances and best cruise in entire cruising phase flight course
Degree.Finally herein by genetic algorithm is used, obtain best cruise altitude under the different optimal fuel mileages of aircraft weight and
Maximum Endurance Mach number.
2. the cruising phase fuel consumption model based on BADA
Annotation table
The fuel consumption of specific thrust in the η unit time, kg/ (minkN)；
Cf1,Cf2First and second specific thrust fuel consumption coefficient；
Single-shot thrust of the T aircraft in cruising phase, kN；
Resistance of the D aircraft in cruising phase, kN；
Lift of the L aircraft in cruising phase, kN；
The quality of m aircraft, kg；
The acceleration of gravity of g aircraft, kg/s2；
VTASFlight true air speed, knots；
V flight relative velocity, knots；
CLLift coefficient；
CDResistance coefficient；
S aircraft wing area, m2；
The total fuel consumption of F, kg；
N engine number of units；
K flight time, s；
T1The corresponding atmospheric temperature of atmospheric density, T0Take 25 DEG C；
paHeight above sea level is the atmospheric pressure of H, Pa；
p0Atmospheric pressure when height above sea level is 0km, takes p0=0.1013MPa；
H height above sea level, Metres；
Atmospheric density when ρ height above sea level is H, kg/m3；
VwindAircraft climbs the wind speed size being subject to, knots；
DwindAircraft climbs the wind speed direction being subject to；
LbkCoordinate conversion matrix of the flight path axis system to body coordinate system；
LbgCoordinate conversion matrix of the earth axes to body coordinate system；
CfcrCruise fuel oil correction factor；
fcrThe fuel consumption of cruising phase unit time, kg/min；
CD0,CD1First, second resistance coefficient；
miThe Aircraft Quality at i moment, kg；
FiThe fuel consumption at i moment, kg；
fcriThe unit time fuel consumption at i moment, kg/min；
Q hours fuel consumption, kg；
M Mach number；
Hj,MjFlying height and Mach number under different weight；
CfcrCruise fuel oil correction factor；
The yaw angle of aircraft cruising phase；
The pitch angle of θ aircraft cruising phase；
The roll angle of φ aircraft cruising phase；
SR fuel mileage.
(1) cruising phase fuel consumption model
The fuel consumption of specific thrust in the turbine jet engine aircraft unit time are as follows:
Aircraft turbine type single-shot fuel consumption in cruising phase are as follows:
fcr=η TCfcr (2)
Wherein, CfcrFor the fuel oil correction factor that cruises, inquiry BADA database can get specific value.
(2) pneumatic and thrust model
Aircraft will receive lift, gravity, resistance and thrust in cruising flight, wherein assuming that cruising phase is all made of
Constant speed is flat to fly into capable flight.It is as follows that thrust, resistance and lift can be obtained according to force analysis:
Wherein resistance coefficient CDIt is modeled by parabola polarity are as follows:
CD=CD0+CD1CL 2 (5)
It can be obtained according to formula (3), (4) and (5):
Wherein CD0, CD1Size for the first, second resistance coefficient, numerical value is determined by test flight data fitting, can be led to
It crosses and consults the specific value that BADA database obtains different type of machines.It can be obtained by model above each in cruising phase flight course
The fuel consumption at moment can obtain the fuel consumption of entire cruising phase, formula by being superimposed are as follows:
(3) meteorologic factor
Atmosphere is one layer of admixture of gas for surrounding the earth, and major parameter is pressure, temperature, density, these parameter values
It changes greatly in vertical direction and more uniform in the horizontal plane, as height increases, temperature is reduced, atmospheric density becomes smaller, empty
Gas is easily compressed, and the utilization of thermal energy is improved, and fuel consumption rate reduces.The pass of height above sea level and atmospheric temperature, pressure and density
It is formula:
T1=T0-1.98×(H/304.8) (8)
pa=p0(1-0.02257×H×10-3)5.256 (9)
According to calculating formula (8), (9) and (10), the corresponding atmospheric temperature of each cruising altitude, pressure and close can be calculated
Degree.
3. cruising phase fuel consumption Optimized model
The influence of crosswind is added in 3.1 models
Flight environment of vehicle especially crosswind, has larger impact to fuel consumption.Three-dimensional wind will be studied herein to the shadow of flight
It rings, and then studies influence of the three-dimensional wind to fuel consumption.We generally use wind speed size VwindWith wind speed direction DwindTwo
Parameter describes wind, and wherein wind speed direction is positive clockwise with Taoist scripture line direct north for 0 °.It, can by inquiring meteorological data
To obtain the wind data of different regions different height, including wind speed size and wind speed direction.
To study influence of the three-dimensional wind to aircraft flight, it is necessary first to according to wind speed size VwindWith wind speed direction Dwind, meter
Calculation obtains projection vector [u of the wind speed in earth axeswg vwg wwg]T, it may be assumed that
uwg=VwindcosDwind (11)
vwg=VwindsinDwind (12)
wwg=0 (13)
When having crosswind, at [u v w]TThe relative velocity V of aircraft in body coordinate system are as follows:
(14)
Wherein, LbgAre as follows:
[uwg vwg wwg]TIt can be calculated by formula (11), (12) and (13).That is the relative velocity of aircraft are as follows:
The influence of mass change is considered in 3.2 models
Although described above be based on BADA database cruising phase fuel consumption model, it is contemplated that crosswind, temperature, pressure
Influence of the strong and density to fuel consumption, is more in line with true environment, improves model prediction accuracy.But in the model not
Consider influence of the variation of quality to fuel consumption, and large-scale airline carriers of passengers cruising flight phase fuel oil in medium and long distance voyage
Consumption proportion is excessive, more obvious so as to cause influence of the variation to fuel consumption of quality, therefore this chapter is by aircraft
Weight change is added in fuel consumption model and is studied.
Due to fuel consumption generation so that cause Aircraft Quality changing in real time, and based on front model can calculate it is winged
The fuel consumption at machine each moment.The real-time quality that can obtain aircraft is that the quality of previous second subtracts the fuel consumption of previous second
Amount, is expressed as follows:
mi=mi-1-Fi-1 (17)
Formula (18), which are substituted into front fuel consumption model, to be obtained:
Wherein [0, k] i ∈, when i is 1, m0For initial mass of cruising, F0It is 0.
4. carrying out fuel economy analysis based on cruising phase Optimized model
The optimization of 4.1 fuel mileages
Passenger plane cruise efficiency refers to producing level of the passenger plane in cruising phase to fuel oil.Passenger plane consumption unit fuel oil is flown over
Voyage it is longer, or fly over that fuel oil consumed by unit voyage is fewer, and cruise efficiency is higher.Fuel oil and voyage are that reflection is patrolled
Boat most important two parameters of efficiency, therefore select fuel mileage (SR) as the standard for judging cruise efficiency height, combustion herein
Oily mileage is bigger, then aircraft range is bigger, and cruise efficiency is higher.Fuel mileage indicates are as follows:
, the weight, aerodynamic characteristic, flying height and Mach number including passenger plane many because being known as of influence cruise efficiency, with
And size of engine characteristics, wind-force etc..After determining research type, aerodynamic characteristic and engine characteristics are had determined.
Air Passenger A320 type cruising flight height and Mach number and crosswind under different quality variation is discussed herein primarily to imitate cruise
The influence of rate therefrom finds out best cruise altitude corresponding to different flight reappearances and ultimate run Mach number, makes cruise efficiency
Reach maximum.
Firstly, the influence of wind is added in fuel mileage calculating, indicate are as follows:
Then, fuel mileage calculate in hour fuel consumption Q consider Aircraft Quality real-time change, in conjunction with above institute it is excellent
The cruising phase fuel consumption model of change may be expressed as: in turn
In order to acquire optimal fuel mileage and corresponding best cruise altitude and Maximum Endurance Mach under each quality
Number, is now established with drag:
Objective function:
Wherein:
Constraint condition are as follows: 0.5≤M≤0.82
39t≤m≤77t
H=8100,8400,8900,9200,9500,9800,10100,10400,10700,11000,11300,
11600,11900 }
Decision variable are as follows: Hj, Mj, wherein [39,77] j ∈
The design of 4.2 derivation algorithms
It is solved herein using genetic algorithm, it is existing since objective function needs to acquire 39 to 77 tons of optimal solution respectively
Only be discussed in detail 39 tons realization each steps, remaining quality realize the step of it is similar.Detailed process is as shown in Figure 8.
Step 1: initial setting up.First, it would be desirable to which Population Size P, select probability G, crossover probability J, variation are set generally
Rate B and maximum number of iterations M, facilitates in subsequent step and uses.
Step 2: coding and initialization of population.For convenience of the subsequent iterative evolution of chromosome, it is necessary first to carrying information
Chromosome encoded, i.e., under 39 tons of quality flying height and Mach number be separately encoded as H39,M39.It is then based on volume
Code generates corresponding random number, is expressed as Random (H39) and Random (M39), wherein Random (H39) ∈ [8100,8400,
8900,9200,9500,9800,10100,10400,10700,11000,11300,11600,11900], Random (M39)∈
[0.50,0.82], is divided into 0.01.
After generating corresponding random number based on coding, according to the group size P of setting, P chromosome is produced, wherein respectively
Gene in chromosome is that random sequence generates, and initialization of population is completed.
Step 3: calculating individual adaptation degree.After the completion of initialization of population, it would be desirable to calculate adaptation individual in population
Degree facilitates and selects below individual.Since the objective function solved herein is fuel mileage value maximization problems, target letter
Number value is the fuel mileage value under each quality, so the fitness function chosen are as follows:
F (x)=SRj,j∈[39,77]
Step 4: selecting individual.Number of individuals is chosen according to select probability G, it is assumed that select probability 0.9, initially
Number of individuals is 100 in population, then selected number of individuals is 0.9 × 100=90.Selecting object uses the side of random competition
Method chooses a pair of of individual by roulette selection mechanism every time, after allow the two individuals to be at war with, according to front fitness letter
Number calculated results so that the high individual of fitness is selected, repeatedly, until be full 90 until.But what we were arranged
Population number will be 100, therefore also need to replicate 10 high individuals of fitness.
Step 5: cross exchanged portion gene.By the selected individual of previous step, cross exchanged gene is carried out two-by-two,
In each individual can carry out cross exchanged probability depend on crossover probability J.Using common single-point type crossing operation, that is, exist
In flying height and the random sequence of Mach number, the gene of two parent chromosomes is exchanged.
Step 6: making a variation.In order to accelerate algorithm speed and guarantee feasibility individual after making a variation, in cross exchanged portion
After dividing gene, genetic mutation is carried out.According to mutation probability B, using the variation method of exchange genic value, that is, a dye is randomly choosed
Colour solid reselects its corresponding gene.
Step 7: judging whether to meet termination condition.After the completion of the 6th step of front, new population is generated, that is, is completed
First time iteration under 39 tons of quality.Then process of the third to the 6th step, the new population constantly generated, objective function are repeated
Value also gradually becomes excellent.We need to set the number of iterations as the condition terminated.If the number of iterations M is set as 200, if repeatedly
Generation number > 200, then run abort, the target function value under 39 tons of output.Export result after, will according to above step repeat into
Algorithm under remaining quality of row solves, and finally acquires the target function value under 39 to 77 tons of quality.
5. sample calculation analysis
It leaves the theatre the QAR data of certain flight cruising phase firstly, obtaining Qingdao, by flight path data in the QAR data,
It simulates and disappears with the approximate flight path of practical flight, the fuel oil that the variation of the considerations of this chapter is established flight reappearance and crosswind is added
Model is consumed, fuel consumption calculating is carried out, fuel consumption values in the calculated results and QAR data are subjected to accuracy comparison, verifying
Model is feasible.Secondly, calculating the hour fuel oil of different flying heights and different Mach number based on the fuel consumption model optimized
Consumption.Finally, calculating the optimal fuel mileage, most under different weight using two methods (Lingo software and genetic algorithm)
Big voyage Mach number and flight optimization height.
5.1 data acquisitions and preparation
It flight plan way point information is combined by programming, simulates the flight path of aircraft, then by being simulated
Flight path parameter substitutes into fuel consumption model, final to carry out fuel consumption theoretical calculation.
Before progress fuel consumption calculating, it would be desirable to first simulate aircraft flight path, obtain in aircraft flight
The flight parameters such as speed, height, flying distance.It is tested since fuel consumption the calculated results need to be compared with QAR data
Card, so approximate emulation should be carried out according to practical flight track data in QAR in trajectory simulation.From acquired QAR
The data that cruising flight phase is chosen in data select 4 way point information and carry out analogue simulation, wherein the flight speed simulated
Degree, flying height are both needed to QAR data approximation, and way point information of specifically cruising is as shown in table 1.Type A320 is chosen, it is concrete
Energy parameter consults the acquisition of BADA database.
1 cruising phase way point information table of table
Can be seen that by table 1, entire cruising phase state of flight is as follows: aircraft after Top of Climb TOC1, along
B1 way point direction, it is flat winged that flying speed keeps 760km/h, 7200 meters of flying height holding to carry out, and reaches after 132 kilometers of flight
B1 way point；Then along B2 way point direction, flat winged acceleration is carried out, B2 way point is reached after 14 kilometers of flight, flies at this time
Speed reaches 810km/h；Finally along TOD way point direction, flying speed keeps 810km/h, flying height to be kept for 7200 meters
Put down and fly, TOD way point is reached after 174 kilometers of flight, entire cruising flight phase terminates, and total flight path that cruises is
320km。
The flight path of cruising phase can be simulated, is simulated in conjunction with 1 information of table using the computer program of establishment
Flight path information specifically includes simulation time, coordinate points, flying height, flying speed, true air speed and velocity of sound, such as 2 institute of table
Show.
2 simulated flight trace information table of table
It in conjunction with the data in simulated flight trace information, is added in optimized fuel consumption model, can calculate every
The fuel consumption of second.It is calculated in addition, wind is added in fuel consumption model this example, the data acquisition of wind derives from
QAR data.
5.2 experimental verifications consider that Aircraft Quality changes cruising phase fuel consumption model
Related scholar often ignores influence (variation of Aircraft Quality variation when calculating cruising phase fuel consumption model
It is due to caused by the generation of oil consumption).But due to large-scale airline carriers of passengers in medium and long distance voyage cruising flight phase fuel oil
Consumption proportion is larger, therefore ignores Aircraft Quality variation and will lead to cruising phase oil consumption calculating generation large error.Cause
The cruising phase fuel consumption model for considering Aircraft Quality variation has been established in this above, and front is simulated to the parameter come and substitutes into mould
Fuel consumption calculating is carried out in type, calculated result and QAR data comparison are as shown in Figure 1.
Fig. 1 is shown in flight course with every fuel consumption for being divided into a mission phase for 4 seconds, and flight course is
1464 seconds, amount to 366 mission phases.Black curve is the calculated results curve, and grey is QAR data.The curve from figure
From the point of view of tendency, the fuel consumption variation at cruising phase each moment is little, this is because when most of during cruising flight
In be all made of constant flying speed and constant flying height is flown.Due in the cruising flight phase for some time
It is flown using flat winged speedup mode, so causing the oil consumption that timesharing is carved in the middle part of figure that ascendant trend is presented.Two groups of curves are total from figure
From the point of view of body, the calculated results are close to the fuel consumption in QAR data.
Below by 1464 seconds in flight course with 148 seconds be a mission phase, 10 mission phases are divided into, by each rank
The fuel consumption of section carries out that table 3 is calculated.
3 cruising phase theoretical calculation of table and QAR data comparison table (unit: kg)
The model theory calculated result is compared with QAR calculated result by table 3, whether judgment models are feasible.It will be each
It is 979.3kg, entire ramp-up period in QAR data that point fuel consumption addition, which can obtain the total fuel consumption of entire ramp-up period,
Total fuel consumption is 1068kg, and you can get it fuel consumption model is 979.3/ in entire cruising phase counting accuracy
1068*100%=91.7%, counting accuracy are high.It is shown by the accuracy calculated result of each mission phase and to be proposed
It is high in the equal counting accuracy of each mission phase to optimize fuel consumption model, model each inflight phase in cruising phase
Row.
Mass change is considered under 5.3 different flying conditions and does not consider mass change comparative experiments
It is had verified that in the example of front and considers that the cruising phase fuel consumption model accuracy of mass change is high, model can
Row.This experiment calculates the hour fuel consumption under different flying conditions based on the model optimized, and does not consider mass change
The calculated hour fuel consumption comparative analysis of institute.The purpose for designing this experiment is: it is possible, firstly, to calculate consideration quality
Change and do not consider mass change generated hour oil consumption difference under different flying conditions, to verify institute's Optimized model
Necessity.Then, since fuel mileage formula (22) can obtain, calculated hour oil consumption can be the experiment of fuel mileage below
It prepares.
The different flying conditions that this experiment considers are as follows: different flight Mach numbers and different flying heights.We select
The different flight Mach numbers for taking 0.5~0.82 flight Mach number (0.01 flight Mach number of spacing) to consider as this experiment.Due to
The flying height of medium-long range passenger plane is located at 8000~12000 meters and according to reduce vertical spacing standard (RVSM), therefore we select
Take 8100 meters, 8400 meters, 8900 meters, 9200 meters, 9500 meters, 9800 meters, 10100 meters, 10400 meters, 10700 meters, 11000 meters,
11300 meters, 11600 meters, different flying height conditions of 11900 meters of height layers as this experiment.
Firstly, selecting the Air Passenger A320 type that cruise starting weight is 63 tons, constant Mach 0.68 is calculated separately
Consideration mass change corresponding to 8100 meters~11900 meters height layers and do not consider mass change hour fuel consumption, calculates knot
Fruit is shown in Table 4.
The hour fuel consumption table (unit: kg) of 4 cruising phase difference flying height of table
It can be obtained by table 4, under the conditions of constant Mach 0.68, with the increase of flying height, the two difference is gradually
Become larger, hour fuel consumption difference is up to 30kg/h.
Then, we continue to select the Air Passenger A320 type that cruise starting weight is 63 tons, fixed altitudes 11600
Rice, calculates separately consideration mass change corresponding to 0.5~0.82 flight Mach number (0.01 flight Mach number of spacing) and does not consider
Mass change hour fuel consumption, calculated result are shown in Table 5.
5 cruising phase flying height of table is the hour fuel consumption table (unit: kg) of 11600 meters of different Mach numbers
It can be obtained by table 5, under the conditions of 11600 meters of fixed altitudes, with the increase of flight Mach number, the two difference
It is gradually reduced, hour fuel consumption difference is up to 47kg/h.
Can be obtained by above two table analysis, consider mass change compared with not considering mass change hour fuel consumption,
The considerations of difference is obvious, that is, optimized mass change cruising phase fuel consumption model very it is necessary to.
Since cruising phase hour fuel consumption is by different Mach number and different flying height joint effects, and front
Hour combustion corresponding to different cruising flight height under the conditions of only calculating fixed flight Mach number 0.68 with the model optimized
Hour fuel consumption corresponding to different cruising flight Mach numbers under the conditions of oilconsumption and 11600 meters of fixed altitudes
Amount now needs to calculate hour fuel consumption corresponding to different flight Mach numbers, different flying heights.Some numerical results are shown in Table 6.
The hour fuel consumption table (unit: kg) of 6 cruising phase difference flying condition of table
By calculating in table as a result, we can obtain Air Passenger A320 type difference flight Mach when considering mass change
Hour fuel consumption corresponding to number, different flying heights.Dispatch person predicts flight often through production flight plan
Fuel consumption, the above calculated result can help dispatch person by the hour fuel consumption under inquiry different condition come to cruise
Stage is accurately predicted, improves prediction accurately, aircraft vehicle is avoided to cross multiple fuel, and then leads to the hair of " oil consumption oil " phenomenon
It is raw.
Cruising flight Mach number, flying height and hour fuel consumption values 3-D image are as shown in Figure 2.
Hour fuel consumption values corresponding to different cruising flight Mach numbers, different flying heights can be intuitively found out by Fig. 2.Root
It can be obtained according to image tendency, under constant Mach, hour fuel consumption values are reduced with the increase of flying height, this is because with
The increase of flying height, atmospheric density is lower, and resistance is smaller, so that thrust is smaller, a hour oil consumption is finally made to become smaller；And it fixes
Under flying height, hour fuel consumption values increase with the increase of flight Mach number, this is because flight Mach number increases, true air speed
Become larger, so that motor power increases, increases hour oil consumption.It is high in different flight Mach numbers, different flights
Under the collective effect of degree, hour fuel consumption values reach maximum under conditions of flight Mach number is 0.82, flying height is 8100 meters
Value is 3217kg.
The analysis of 5.4 fuel economy
The fuel economy of cruising phase is mainly studied in this experiment, using fuel mileage as economic index, is calculated different
Fuel mileage, Maximum Endurance Mach number and best cruise altitude under weight.
5.4.1 fixed initial cruise Economics of Quality analysis
This research considers initially to cruise quality first for 63 tons of Air Passenger A320 type, calculates different flying heights under the weight
Fuel mileage of the layer (8100~11900 meters) in different Mach number (0.5~1.0).A certain height layer is calculated first in different horses
It is conspicuous it is several under fuel mileage, as height layer first chooses 8100 meters.It can be obtained according to fuel mileage formula (22), fuel mileage is ground velocity
With the result of the quotient of hour fuel consumption.Hour fuel consumption under different condition has been calculated by front example, and
And the ground velocity for considering that crosswind influences can be calculated by formula (17), so that the fuel mileage under different condition can calculate
It obtains.8100 meters of flying heights are as shown in Figure 3 in the fuel mileage calculated result of different flight Mach number conditions.
As can be seen from Figure 3, under 8100 meters of flying heights, with the increase of flight Mach number, fuel mileage first increases
After reduce, reach maximum value in 0.64 Mach number fuel mileage, be 0.176229kgkm-1.This variation tendency be due to
The increase of flight Mach number, true air speed and ground velocity increasing, also increasing so as to cause hour fuel consumption.According to combustion
Oily mileage calculation formula can obtain molecule, denominator and increase, but increasing degree is different, first increases so as to cause fuel mileage value
After reduce.
The fuel mileage value that different height layer (8400~11900 meters) changes with flight Mach number is according to same side
Method, which calculates, to be obtained, and final calculation result is as shown in Figure 4.
Figure 4, it can be seen that with the increase of flight Mach number, the corresponding fuel mileage of different flying heights first increases
After reduce.With the variation of flight Mach number under 8400~11900 different flying heights, optimal fuel mileage and it is corresponding most
Big cruise Mach number is shown in Table 7.
Optimal fuel mileage of the different flying heights of table 7 in different flight Mach number conditions
Optimal fuel mileage value and the corresponding Maximum Endurance Mach under different flying heights can be obtained according to table 7
Number.
We can draw the 3-D image of fuel mileage, flight Mach number and flying height according to data, such as Fig. 5 institute
Show.
Fuel mileage corresponding to different flight Mach numbers and different flying heights can be intuitively found out by Fig. 5 and table 7
Value, finding the maximum point of fuel mileage value is optimal fuel mileage value, to find corresponding best cruising flight height
And Maximum Endurance Mach number.The optimal fuel mileage value of this experiment is 0.212, and corresponding best cruise altitude is 11900 meters,
Maximum Endurance Mach 2 ship 0.8.
5.4.2 different initial cruise Economics of Quality analyses
It is optimal fuel mileage value corresponding to 63 tons, best cruise that Air Passenger A320 has been studied in initially cruise quality in front
Height and Maximum Endurance Mach number.Different initial cruise Economics of Qualities are analyzed on the basis of this experiment in front.It looks into
Readding BADA database can obtain, and Air Passenger A320 empty mass is 39 tons, and being fully loaded with quality is 77 tons.This trifle will use two methods
(Lingo software and genetic algorithm) calculates the optimal fuel mileage value and corresponding best cruise altitude, most of different quality
Big cruise Mach number.
(1) Lingo software calculation method: Lingo software, setting is added in the fuel mileage Optimized model that front is established
Constraint condition is calculated.Specific calculated result is shown in Table 8.
Optimal fuel mileage value (calculating of Lingo software) corresponding to 8 A320 difference of table cruise quality
Optimal fuel mileage value corresponding to different initial cruise quality can be obtained by table 8 and fuel economy is optimal
When flight Mach number (Maximum Endurance Mach number) and cruising altitude (best cruise altitude).By different initial cruise quality and
Corresponding Maximum Endurance Mach number, best cruise altitude are established three-dimensional relationship figure and are indicated, such as Fig. 6.
By Fig. 6 and table 8 can intuitively obtain Air Passenger A320 in different initial cruise quality flight it is corresponding most
Big cruise Mach number, best cruise altitude.Controller and pilot can be according to result above, according to the different cruise matter of aircraft
Amount, makes aircraft according to corresponding best cruise altitude and Maximum Endurance Mach number, so that fuel economy be reached
It is optimal.
(2) it is solved using genetic algorithm: based on previously described, now being solved using genetic algorithm.Firstly, setting
Population Size P is 100, and select probability G is 0.9, and crossover probability J is 0.9, and mutation probability B is 0.1 and maximum number of iterations M
It is 200.Then coding solution is carried out, what is obtained the results are shown in Table 9.
Flight optimization condition (genetic algorithm) corresponding to 9 A320 difference of table cruise quality
The Maximum Endurance Mach corresponding to quality that Bu Tong initially cruises that will be solved using Lingo software with genetic algorithm
Number, best cruise altitude establish three-dimensional relationship figure and compare expression, such as Fig. 7.
By table 7 and table 8 compares and Fig. 7, can obtain using Lingo software and be deposited using the result that genetic algorithm obtains
In smaller difference, this is because the result that genetic algorithm solves may not be optimal solution, but in close proximity to optimal solution.
6. conclusion
It is main herein to study the following contents: firstly, since large-scale airline carriers of passengers cruises in medium and long distance voyage at this stage
Mission phase fuel consumption proportion is excessive, so needing to consider the variation of quality to fuel oil when predicting fuel consumption
Influence.Herein by the cruising phase fuel consumption model based on BADA database is established, do not examined by analysis model itself
Consider influence of the mass change to fuel consumption, improvement is optimized in this chapter: mass change is added in fuel consumption model.It will
Calculated result is compared with QAR data, and as a result accuracy is 91.7%, and verifying model is feasible.Then, based on the cruise optimized
Phase fuel consumption models calculate the hour fuel consumption of different flight Mach numbers and different flying heights, pass through calculating
As a result the hour fuel consumption under different flying conditions can be obtained.The hour that will be considered mass change with do not consider mass change
Fuel consumption calculates separately out, seeks difference, can show that the two difference maximum can reach 47kg, thus prominent institute's Optimized model
Necessity.Finally, calculating aircraft in quality institute of Bu Tong initially cruising by two methods (Lingo software and genetic algorithm)
Corresponding optimal fuel mileage value, best cruise altitude and Maximum Endurance Mach number.Obtaining for the data can pass through controller
It cooperates with pilot, so that aircraft flies under the conditions of best cruise altitude, Maximum Endurance Mach number, so as to cause the combustion of aircraft
Oily mileage value is optimal, and economy is best.
The above examples only illustrate the technical idea of the present invention, and this does not limit the scope of protection of the present invention, all
According to the technical idea provided by the invention, any changes made on the basis of the technical scheme each falls within the scope of the present invention
Within.
Claims (7)
1. a kind of cruising phase fuel consumption prediction technique of flight reappearance variation, it is characterised in that include the following steps:
Step 1, consider the influence of mass change and crosswind, construct cruising phase fuel consumption model；
Step 2, the model constructed for step 1, establishes objective function and constraint condition；
Step 3, the optimal solution for solving objective function obtains optimal fuel mileage and corresponding best cruise under each quality
Height and Maximum Endurance Mach number.
2. the method as described in claim 1, it is characterised in that: in the step 1, the cruising phase fuel consumption model of building
It indicates are as follows:
Wherein, Q is hour fuel consumption；N is engine number of units；Cf1,Cf2Respectively the first and second specific thrust fuel consumption system
Number；VTASFor flight true air speed；CD0,CD1Respectively the first, second resistance coefficient；The atmospheric pressure that ρ is height above sea level when being H；S
For aircraft wing area；V is aircraft relative velocity；mi-1For (i-1)-th second Aircraft Quality；Fi-1Fuel oil for (i-1)-th second disappears
Consumption；G is the acceleration of gravity of aircraft；CfcrFor the fuel oil correction factor that cruises.
3. method according to claim 2, it is characterised in that: in the step 2, the objective function of foundation is:
Wherein:
Constraint condition are as follows: 0.5≤M≤0.82
39t≤m≤77t
H=8100,8400,8900,9200,9500,9800,10100,10400,10700,
11000,11300,11600,11900 }
Decision variable are as follows: Hj, Mj
Wherein, Hj, MjRespectively indicate corresponding flying height and Mach number when Aircraft Quality is j.
4. method as claimed in claim 3, it is characterised in that: in the step 3, solved using genetic algorithm, according to
Following steps solve the optimal solution of corresponding each quality j ∈ [39,77]:
The first step, setting Population Size P, select probability G, crossover probability J, mutation probability B and maximum number of iterations M；
Second step, to carry information chromosome encode, i.e., under each quality j flying height and Mach number compile respectively
Code is Hj, Mj；It is then based on coding and generates corresponding random number, be expressed as Random (Hj) and Random (Mj), wherein Random
(Hj) ∈ [8100,8400,8900,9200,9500,9800,10100,10400,10700,11000,11300,11600,
11900], Random (Mj) ∈ [0.50,0.82], it is divided into 0.01；
Corresponding random number is generated based on coding, according to the Population Size P of setting, P chromosome is generated, wherein in each chromosome
Gene be random sequence generate；
Third step calculates fitness individual in population；
4th step chooses number of individuals according to select probability G；
The 4th selected individual of step is carried out cross exchanged gene by the 5th step two-by-two, wherein each individual carries out cross exchanged
Probability depend on crossover probability J；
Step 6: carrying out genetic mutation according to mutation probability B using the variation method of exchange genic value, that is, randomly choosing one
Chromosome reselects its corresponding gene；
7th step finally acquires the target function value under 39 to 77 tons of quality using the number of iterations as termination condition.
5. method as claimed in claim 4, it is characterised in that: in the third step, choose following fitness function:
F (x)=SRj,j∈[39,77]
Wherein, the expression formula of fuel mileage SR are as follows:
Wherein, VTASFor flight true air speed；Q is hour fuel consumption.
6. method as claimed in claim 4, it is characterised in that: in the 4th step, selecting object uses the side of random competition
Method chooses a pair of of individual by roulette selection mechanism every time, then allows the two individuals to be at war with, according to front fitness
Function calculated result, so that the high individual of fitness is selected, repeatedly, until be full (number of individuals in G × initial population)
Until a, (in initial population in number of individuals-G × initial population number of individuals) a fitness high individual is then replicated again.
7. method as claimed in claim 4, it is characterised in that: in the 5th step, using common single-point type crossing operation,
I.e. in flying height and the random sequence of Mach number, the gene of two parent chromosomes is exchanged.
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