CN112085145A - Method for designing control law of mode conversion process of self-adaptive circulating aero-engine - Google Patents

Method for designing control law of mode conversion process of self-adaptive circulating aero-engine Download PDF

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CN112085145A
CN112085145A CN202010925495.4A CN202010925495A CN112085145A CN 112085145 A CN112085145 A CN 112085145A CN 202010925495 A CN202010925495 A CN 202010925495A CN 112085145 A CN112085145 A CN 112085145A
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张纪元
陈敏
唐海龙
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Abstract

The invention discloses an automatic design method of a mode conversion process control rule of a self-adaptive cycle engine. According to the method, the mode conversion design is simplified from a working process to research of two key working points, the particle swarm optimization algorithm is combined with the sensitivity analysis method to solve the control law of the key working points, the control law of the whole mode conversion process is further obtained, manual adjustment is not needed in the process of solving the control law, and the design efficiency can be greatly improved.

Description

Method for designing control law of mode conversion process of self-adaptive circulating aero-engine
Technical Field
The invention belongs to the technical field of overall performance simulation of an adaptive cycle aero-engine, and particularly relates to automatic design of a control rule of a mode conversion process.
Background
The self-adaptive cycle aircraft engine is a strategic and technical plateau pursued by the strong country competition of the international aircraft engine at present, and is the extension and development of the concept of the double-connotation variable cycle aircraft engine. The self-adaptive circulating aero-engine flexibly adjusts the circulating mode and circulating parameters of the engine through adjustable mechanisms such as a mode selection valve, an adjustable guide vane of a rotating part, a variable-area bypass ejector and a spray pipe, so that the engine can automatically adapt to the flight of an airplane in a wider speed domain and airspace range, and the more rigorous performance requirements of different flight tasks on the engine are met.
Compared with a variable-cycle engine, the self-adaptive cycle engine is additionally provided with a third bypass, and by closing one or more outer bypasses, the self-adaptive cycle engine can work in a double bypass or single bypass mode with a low bypass ratio to generate larger unit thrust so as to meet the requirement of large thrust during the supersonic cruise and combat maneuver flight of an airplane; on the other hand, the self-adaptive cycle engine can work in a three-bypass mode with a large bypass ratio by opening the three external bypasses, so that the oil consumption rate is reduced, and the low oil consumption requirements of the airplane during subsonic cruising and air patrol are met. The adaptive cycle engine needs to operate in a number of different modes throughout the mission and therefore inevitably undergoes a mode transition process.
Mode transition refers to the adaptive engine transitioning from one stable operating mode to another. The control law refers to an adjusting scheme of controlled objects such as fuel oil, rotating speed, adjustable components and the like which guarantee stable and efficient work of the engine; the fuel or the rotating speed is one type of controlled object and is referred to as a main control object, and the adjustable component is another type of controlled object. The design problem of the mode conversion process control law specifically refers to that: under the conditions of engine control rules and working conditions of a given mode conversion starting point and ending point, the control rules in the intermediate process are reasonably designed, so that the mode conversion is stably completed. During the mode conversion process, part of the ducts can be subjected to on/off state switching, so that the flow distribution inside the engine is greatly changed. Especially for the component of the mode selection valve with only two modes of opening/closing, the adjustment is a process which is completed instantly, and the matching work of the engine is influenced along with the step of the second bypass flow. Therefore, a reasonable control rule of the adjustable components needs to be formulated in the mode conversion process, and risks such as over-temperature, over-rotation and surge of the engine are avoided through the cooperative adjustment of the adjustable components. In addition, in order to ensure the mode conversion process to be smoothly carried out, the flow of the engine is required to be basically kept unchanged in the mode conversion process, and the thrust is stably changed without obvious step in the mode conversion process. In conclusion, the design of the control law of the mode conversion process is an optimization problem of multi-constraint multivariable, which also becomes one of the most complex problems in the design of the control law of the adaptive cycle engine, and the design difficulty is higher than that of the control law under a single working condition.
The current research on the mode conversion control law of the adaptive cycle engine is in the preliminary stage, and the problem is not discussed in detail in the published literature. The mode conversion control rule design of the double-foreign-content variable-cycle engine is the closest to the problem, and some domestic scholars develop related researches on the problem. However, the design of the control law in the related research is obtained based on manual debugging of researchers, the debugging process is complex and tedious, and the researchers are required to have strong professional knowledge; in addition, the control law obtained by manual debugging is closely related to the current engine design parameters and component characteristics, and when the design parameters or the component characteristics are changed, the original control law is not universal and needs to be manually debugged again. At the beginning of the design of an engine scheme, iterative design of engine design parameters and component characteristics needs to be carried out for many times, and the complexity of manually debugging and controlling rules seriously restricts the efficient development of the design process. On the other hand, the control law of the mode switching process is researched by continuously adjustable components, and a mode selection valve, which is a component with only two states of opening/closing, is not considered. The transient switching of the on/off state of the mode selection valve can cause a second bypass flow step, so that the thrust and the flow step of the engine are easily caused, the stable operation of the mode switching process of the engine is obviously influenced, and important research needs to be carried out in the design of a control law.
Disclosure of Invention
Aiming at the defects of the existing mode conversion control rule design method of the self-adaptive cycle aircraft engine, the invention provides an automatic mode conversion control rule design method based on a particle swarm optimization algorithm and a sensitivity analysis method. The specific technical scheme of the invention is as follows:
a method for designing a control law of a mode conversion process of a self-adaptive circulation aero-engine is characterized in that,
the mode conversion process is simplified into two important working conditions: the mode selection valve state is a critical point before mode conversion before switching, and the mode selection valve state is a critical point after mode conversion after switching;
the two important working conditions divide the mode conversion process into three stages, namely a stage of adjusting before mode conversion from a mode conversion starting point to a mode conversion front critical point, a stage of adjusting before mode conversion from the mode conversion front critical point to a mode conversion rear critical point, a stage of adjusting after mode conversion from the mode conversion rear critical point to the mode conversion end point,
specifically, the design method comprises the following steps:
s1: setting working condition parameters and control rules of a mode conversion starting point and an end point of the self-adaptive cycle aero-engine, inputting the working condition parameters and the control rules into an engine component level performance simulation model for calculation, and obtaining the performance of the starting point and the end point of the engine; given constraint conditions which need to be met by the engine performance in the mode conversion process;
s2: it is checked whether the performances of the start point and the end point of the engine mode transition obtained in step S1 satisfy the constraints of the mode transition process: if the constraint condition is not met, outputting a prompt that the working condition and/or the control rule of the mode conversion starting point and/or the mode conversion ending point need to be changed, and ending the design process; if the constraint condition is met, the step S3 is carried out to design the control rule of the critical point before the mode conversion;
s3: the design of a control rule of a critical point adjustable component before mode conversion is carried out by utilizing a particle swarm optimization algorithm, the optimization aim is to reduce the difference between the critical point before mode conversion and a mode conversion termination point, reduce the change of the thrust at the moment of state switching of a mode conversion valve so as to ensure that the mode conversion is carried out stably, and simultaneously meet the constraint condition of the mode conversion process;
s4: switching the on-off state of the mode conversion valve, calculating the performance of the engine, and checking whether the performance of the engine meets the constraint condition of the mode conversion process: if the condition is met, obtaining a control rule of the critical point after the mode conversion, and turning to step S6 to design the control rule of the pre-mode conversion adjusting stage and the post-mode conversion adjusting stage; if not, the process goes to step S5;
s5: solving a control rule of the critical point after the mode conversion by using sensitivity analysis, developing sensitivity analysis aiming at the constraint condition of the unsatisfied mode conversion process, analyzing the influence of the adjustment of the adjustable component on the constraint condition, and sequentially adjusting the adjustable component according to the influence degree until the constraint condition of the mode conversion process is satisfied, namely obtaining the control rule of the critical point after the mode conversion;
s6: based on the critical point control rule before mode conversion obtained in step S3 in combination with the mode conversion starting point control rule, a control rule of the adjustment stage before mode conversion is obtained by using linear interpolation; based on the control law of the critical point after the mode conversion obtained in the step S4 or the step S5 and the control law of the mode conversion termination point, the control law of the adjustment stage after the mode conversion is obtained by utilizing linear interpolation;
s7: and outputting a control rule design result of the mode conversion process.
Further, the method of step S3 is:
s3-1: initial positions, initial velocities and normalized definitions of m particles are randomly generated as shown in equations (1), (2) and (3), respectively:
Figure BDA0002666389500000031
Figure BDA0002666389500000032
Figure BDA0002666389500000033
wherein i representsi particles; j represents the jth iteration;
Figure BDA0002666389500000034
for the position of the jth iteration of the ith particle,
Figure BDA0002666389500000035
represents the normalized value of the nth tunable component,
Figure BDA0002666389500000036
for the normalized value of the 1 st adjustable component of the ith particle of the jth iteration,
Figure BDA0002666389500000041
for the normalized value of the 2 nd adjustable component of the ith particle of the jth iteration,
Figure BDA0002666389500000042
normalizing the value of the nth adjustable component of the ith particle in the jth iteration;
Figure BDA0002666389500000043
for the speed of the jth iteration of the ith particle,
Figure BDA0002666389500000044
representing the normalized rate of change of value of the nth tunable component,
Figure BDA0002666389500000045
the normalized rate of change of value of the 1 st adjustable component for the ith particle of the jth iteration,
Figure BDA0002666389500000046
the normalized rate of change of value of the 2 nd adjustable component for the ith particle of the jth iteration,
Figure BDA0002666389500000047
normalized variation rate of value, VG, of the nth tunable element for the ith particle of the jth iterationn,0Representing the current value of the nth tunable element,VGn,minrepresenting the lower limit of the value of the nth adjustable component, VGn,maxRepresents the upper limit of the value of the nth adjustable component;
s3-2: calculating the particle fitness; constructing a fitness function by linear weighting and comprehensively considering an optimization target and a constraint condition
Figure BDA0002666389500000048
Figure BDA0002666389500000049
Wherein: tag represents the optimized target value, PF1Represents the value of the 1 st penalty function, PF2Represents the value of the 2 nd penalty function, PFtRepresents the value of the t-th penalty function, w1Weight coefficient, w, representing the 1 st penalty function2Weight coefficient, w, representing the 2 nd penalty functiontA weighting factor representing the tth penalty function;
s3-3: after the fitness of the current particle is calculated in the step S3-2, the position of the optimal point experienced by the particle is obtained
Figure BDA00026663895000000410
And the location of the optimum point experienced by the entire population
Figure BDA00026663895000000411
Checking the best point experienced by the current population
Figure BDA00026663895000000412
Whether the optimization requirements are met or not, if so, according to the optimal point
Figure BDA00026663895000000413
Calculating to obtain an adjustable component control rule of a critical point before mode conversion; if the particle searching speed does not meet the requirement and the iteration number does not exceed the upper limit, the step S3-4 is carried out to update the particle searching speed;
s3-4: the search speed of the particle is updated using equation (5):
Figure BDA00026663895000000414
wherein the content of the first and second substances,
Figure BDA00026663895000000415
the speed of the j +1 th iteration of the ith particle; c. C1,c2Is an acceleration factor with a value range of [0,4 ]]；r1,r2Is [0,1 ]]A random number within a range; w is a(j)The dynamic inertia factor is represented, the value is (0,1), and a fixed value or a dynamic value can be taken;
s3-5: updating according to the formula (6) to obtain the position of the next generation of particles, and then turning to the step S3-2 to perform a new iteration;
Figure BDA00026663895000000416
wherein the content of the first and second substances,
Figure BDA00026663895000000417
is the position of the j +1 th iteration of the ith particle.
Further, the specific process of step S5 is as follows:
the sensitivity analysis is evaluated by calculating function variation caused by unit variation of the variable, and the sensitivity analysis of the constraint condition on the adjustable component is calculated as shown in the formula (7):
Figure BDA0002666389500000051
wherein Senr,sRepresenting sensitivity of the r-th constraint to the s-th adjustable component, Resr,0Representing the value of the r-th constraint condition, Res, after the adjustment of the s-th adjustable elementr,oriRepresenting the value of the r-th constraint condition before the adjustment of the s-th adjustable component,
Figure BDA0002666389500000052
represents the s th canNormalizing the adjustment quantity of the adjustment component;
after the adjustable component is selected by sensitivity analysis, the value of the adjustable component is obtained by utilizing a dichotomy, and the method comprises the following specific steps:
s5-1: adjusting the adjustable component according to a given step length until a mode conversion process constraint condition is met for the first time, and obtaining an interval consisting of a current adjustable component value and an adjustable component previous point value, and recording the interval as [ a, b ];
s5-2: if the value of the adjustable component is a, the constraint condition is met, and the step is switched to the step S5-3; otherwise, go to step S5-4;
s5-3: setting the value of the adjustable component as (a + b)/2, substituting the value into an engine component-level simulation model to solve the engine performance;
if the engine performance satisfies the constraint condition, setting a to (a + b)/2 to obtain a new interval [ a, b ], and going to step S5-5;
if the engine performance does not satisfy the constraint condition, setting b to (a + b)/2 to obtain a new interval [ a, b ], and going to step S5-5;
s5-4: setting the value of the adjustable component as (a + b)/2, substituting the value into an engine component-level simulation model to solve the engine performance;
if the engine performance satisfies the constraint condition, setting b to (a + b)/2 to obtain a new interval [ a, b ], and going to step S5-5;
if the engine performance does not satisfy the constraint condition, setting a to (a + b)/2 to obtain a new interval [ a, b ], and going to step S5-5;
s5-5: checking whether the width of the new interval [ a, b ] meets the requirement of iteration precision;
if the accuracy is met, the step S5-6 is carried out, and the control rule of the critical point after the mode conversion is output;
if the accuracy requirement is not met, the step S5-2 is carried out to continue iteration;
s5-6: when the value of the adjustable component is a, the constraint condition is met, and the value of a is taken as the value of the critical point of the adjustable component after mode conversion; otherwise, taking the value of b as the value of the critical point of the adjustable component after mode conversion; when all the constraint conditions are met, the control rule of the critical point after the mode conversion is obtained.
Further, the specific process of step S6 is as follows:
presetting interpolation points, calculating interpolation step length by using a formula (8), and obtaining the value of an adjustable component of the interpolation point by using a formula (9);
Figure BDA0002666389500000061
Figure BDA0002666389500000062
wherein Δ VGkRepresents the interpolation step of the kth adjustable component, k is 1,2, … n; VGk,startRepresenting the value of the interpolation starting point of the kth adjustable component, VGk,endRepresenting the value of an interpolation termination point of the kth adjustable component, and num represents the number of the interpolation points; VG(q)The value of the adjustable component representing the qth interpolation point; in particular VG1,startThe value of the interpolation starting point of the 1 st adjustable component is represented, and delta VG1Represents the interpolation step length of the 1 st adjustable component; VG2,startThe value of the interpolation starting point, Δ VG, representing the 2 nd tunable component2Represents the interpolation step size of the 2 nd adjustable component; VGn,startRepresenting the value of the interpolation starting point of the nth adjustable component, Δ VGnRepresents the interpolation step length of the nth adjustable component;
in the process of solving the control law of the pre-adjustment stage and the post-adjustment stage of the mode conversion by using the linear interpolation, when the constraint condition of the mode conversion process is not met, the method which is the same as the design of the control law of the post-mode conversion critical point is adopted: firstly, finding out an adjustable component with the largest influence on the constraint adjustment of the mode conversion process through a sensitivity analysis method, preferentially adjusting the adjustable component, solving the control rule of the adjustable component by utilizing a dichotomy until all constraint conditions are met, and finally realizing the stable operation of the mode conversion process.
Further, in step S1, the master control object is selected as the low-pressure shaft physical rotation speed in the component-level simulation model, and the control law is set to ensure that the low-pressure shaft physical rotation speed is not changed.
Further, in step S1, the constraint conditions that the engine performance needs to meet during the mode switching process include that the rotation speed is lower than the set upper limit, the important section gas temperature is lower than the set upper limit, the component surge margin is higher than the set upper limit, the thrust step is lower than the set upper limit, and the flow rate variation range is lower than the set upper limit.
The invention has the beneficial effects that:
1. the method can realize the automatic design of the control law in the mode conversion process, and avoids the complexity and the low efficiency of manually adjusting the design control law; by utilizing the particle swarm algorithm to design the control rule of the critical point before mode conversion, the difference between the critical point before mode conversion and the mode conversion termination point is reduced, and the risk of engine performance step when the state of the mode selection valve is switched is reduced.
2. According to the invention, the control rule design of the critical point after mode conversion is developed through sensitivity analysis, and the stable switching of the mode selection valve state is realized by adjusting as few adjustable components as possible, which is beneficial to reducing the complexity of the control system design.
3. According to the method, after the control law of the mode conversion front/rear critical point is obtained, the control laws of the mode conversion front adjusting stage and the mode conversion rear adjusting stage are solved by utilizing linear interpolation, the control laws which do not meet the constraint conditions in the mode conversion front adjusting stage and the mode conversion rear adjusting stage are corrected through sensitivity analysis, the automatic design of the mode conversion whole-process control law is finally realized, the mode conversion process is guaranteed to be stably carried out, and the design efficiency of the control law is improved.
Drawings
In order to illustrate embodiments of the present invention or technical solutions in the prior art more clearly, the drawings which are needed in the embodiments will be briefly described below, so that the features and advantages of the present invention can be understood more clearly by referring to the drawings, which are schematic and should not be construed as limiting the present invention in any way, and for a person skilled in the art, other drawings can be obtained on the basis of these drawings without any inventive effort. Wherein:
FIG. 1 is a schematic representation of a prior art adaptive cycle aircraft engine;
FIG. 2 is an exploded view of the adaptive cycle aircraft engine mode transition process of the present invention;
FIG. 3 is an algorithm flow diagram of the mode transition process control law design routine of the present invention;
FIG. 4 is a flow chart of the particle swarm algorithm-based critical point control law optimization algorithm before mode conversion;
FIG. 5 is a flow chart of the critical point control law design algorithm after mode conversion based on sensitivity analysis of the present invention;
FIG. 6 is a control law of an adjustable component (adjustable vane angle) in a mode switching process according to an embodiment of the present invention;
FIG. 7 is a diagram of the control law of the adjustable components (adjustable component area coefficients) in the mode switching process according to an embodiment of the present invention;
FIG. 8 is a graph of engine performance change during mode transitions of an embodiment of the present invention;
FIG. 9 is a graph of engine component surge margin variation during a mode transition of an embodiment of the present invention;
FIG. 10 is a graph of engine component versus scaled rotational speed change during a mode transition of an embodiment of the present invention.
The reference numbers illustrate:
1-a first culvert; 2-second culvert; 3-third culvert; 4-front fan; 5-Flade; 6-mode selector valve; 7-front duct ejector; 8-core machine driven fan; 9-a high-pressure compressor; 10-a low pressure turbine; 11-a rear duct ejector; 12-tail nozzle.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments of the present invention and features of the embodiments may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a schematic structural diagram of an adaptive-cycle aircraft engine, illustrating a bypass structure and main adjustable components of the adaptive-cycle aircraft engine. Compared with a variable-cycle aero-engine, the adaptive-cycle aero-engine is additionally provided with a third culvert 3, 1 'Flade' (Fan + Blade) stage is adopted in a second-stage Fan of the adaptive-cycle aero-engine to extend out of a third culvert, and a stator guide vane is independently adjustable, so that the adaptive-cycle aero-engine can adjust the cycle more greatly. The Flade guide vanes may control the switching of the third culvert 3 and the mode select valve 6 may control the switching of the second culvert 2. Through the combination of different switches of the outer duct, the adaptive cycle aircraft engine in fig. 1 has four different working modes: a triple culvert mode (M3 mode) in which three culvert are all open; a double culvert mode (M13 mode) in which only the second culvert is closed; a double culvert mode (M2 mode) in which only the third culvert is closed; single culvert mode (M1 mode) with both the second culvert and the third culvert closed. By closing one or more outer ducts, the self-adaptive circulation aero-engine can work in a double-duct or single-duct mode with a low duct ratio to generate higher unit thrust so as to meet the requirement of high thrust during the supersonic cruise and combat maneuver flight of the airplane; on the other hand, the self-adaptive circulating aircraft engine can work in a three-bypass mode with a large bypass ratio by opening the three external bypasses, so that the oil consumption rate is reduced, and the low oil consumption requirements of the aircraft during subsonic cruising and air patrol are met. The adaptive cycle aircraft engine needs to operate in a number of different modes throughout the flight mission and therefore inevitably undergoes a mode transition process.
The technical problems to be solved by the design of the mode conversion process control law are mainly as follows: known conditions for designing the control law of the mode conversion process are engine working condition parameters (flight height and flight speed) and the control law (comprising a main control law and an adjustable component value) of a mode conversion starting point and a mode conversion ending point, and the control law in the process of converting the starting point to the ending point is required to be solved. The mode conversion process is simplified into two important working conditions, namely two working conditions before and after the on/off state of the mode selection valve is switched, and the two working conditions are recorded as a critical point before mode conversion and a critical point after mode conversion. The above two important conditions divide the mode conversion process into three stages, which are a pre-mode conversion adjustment stage, a mode conversion intermediate stage, and a post-mode conversion adjustment stage, as shown in fig. 2. After the design of the control rule of the mode conversion front/rear critical point is finished, the mode conversion middle stage can be stably carried out; the control rules of the adjustment stage before mode conversion and the adjustment stage after mode conversion can be obtained by interpolating the control rules of the mode conversion starting/ending point and the mode conversion front/rear critical point, thereby achieving the purpose of automatically finishing the design of the control rules.
FIG. 3 is an algorithm flow chart of a design program for control laws for a mode switching process of the present invention, which automatically calculates control laws for a mode switching process after values of adjustable components at a start point and an end point of the mode switching process are given. According to the method, the mode conversion design is simplified from a section of working process to research of two key working points, the particle swarm optimization algorithm is combined with the sensitivity analysis method to solve the control law of the key working points, and then the control law of the whole mode conversion process is obtained, manual adjustment is not needed in the process of solving the control law, and the design efficiency can be greatly improved; the method has universality, can be directly applied when design parameters and component characteristics are changed, and can efficiently develop the design of the mode conversion process control rule; the on/off state switching process of the mode selection valve is used as an important working condition to carry out research so as to ensure the mode switching process to be carried out stably.
For the convenience of understanding the above technical aspects of the present invention, the following detailed description will be given of the above technical aspects of the present invention by way of specific examples.
Example 1
The mode conversion process of the adaptive-cycle aircraft engine shown in fig. 1 is taken as an example to illustrate the practical application effect of the method. The mode switching process selects the switching from the M13 mode to the M3 mode, involving the switching of the on-off state of the mode select valve. For ease of description of the tunable components involved in the mode conversion process, they are named in the manner in Table 1.
TABLE 1 Adjustable Components of adaptive cycle aircraft engines
Name of VG1 VG2 VG3
Means of Core machine driven fan guide vane Guide vane of high-pressure compressor Mode selection valve
Name of VG4 VG5 VG6
Means of Rear duct ejector Low pressure turbine vane Tail pipe throat
The adjustment ranges for the adjustable components of the adaptive cycle aircraft engine shown in fig. 1 are shown in table 2. Wherein VG1-VG2The value of (1) represents the angle of the adjustable guide vane, and 0 degree representsThe guide vane is completely opened, and the smaller the numerical value is, the smaller the opening angle of the guide vane is; VG3-VG6A coefficient representing the area of the adjustable component, i.e. the ratio of the opening area to the design area, a larger value indicates a larger opening degree of the adjustable component.
TABLE 2 Adjustable part adjustment Range of adaptive cycle aircraft engines
Adjustable component VG1 VG2 VG3
Adjustment range [-45°,0°] [-30°,0°] 0/1
Adjustable component VG4 VG5 VG6
Adjustment range [0.2,1.2] [0.8,1.2] [0.7,1.3]
In this embodiment, setting the constraint conditions in the mode conversion process includes: the surge margin of the compression components (the compression components comprise a fan 4, a core machine driving fan 8 and a high-pressure compressor 9) is more than 10 percent, and the relative conversion rotating speed is lower than 105 percent; the total inlet temperature of the high-pressure turbine is not more than 2150K; the flow variation range of the whole mode conversion process is not more than 2%; the thrust step does not exceed 2%.
The surge margin SM is defined as shown in equation (10):
SM＝(πs/wac,s)/(π0/wac,0)-1 (10)
wherein, pisRepresenting the pressure ratio, w, corresponding to the surge point of the component at the current converted speedac,sRepresenting the converted flow, pi, corresponding to the surge point of the component at the current converted speed0Representing the current pressure ratio of the component, wac,0Representing the current scaled flow of the component.
Relative conversion speed Nc,relIs as defined in formula (11):
Figure BDA0002666389500000101
wherein N isc,0Representing the current converted speed, Nc,desRepresenting the design point scaled rotation speed.
The engine thrust, inlet flow and total high pressure turbine inlet temperature are expressed in relative values, defined as shown in equations (12) to (14):
Frel＝F0/Fstart (12)
Figure BDA0002666389500000102
Figure BDA0002666389500000103
wherein, FrelRepresenting the relative value of engine thrust, F0Thrust force representing the current state of the engine, FstartA thrust representing a starting point of a mode transition of the engine; w is aa,relRepresenting engine intakeRelative value of the port flow, wa,0Inlet flow, w, representing the current state of the enginea,startAn inlet flow representing a starting point of a mode transition of the engine; t is4,relRepresenting the relative value of the total inlet temperature T of the high-pressure turbine of the engine4,0Total high pressure turbine inlet temperature, T, representative of the current state of the engine4,maxRepresenting the maximum total high pressure turbine inlet temperature.
The specific steps of the design of the mode conversion process control law are described as follows:
s1: and inputting working condition parameters and control rules of the engine at the mode conversion starting point and the mode conversion ending point, and calculating the engine performance of the starting point and the ending point working conditions. In order to ensure that the flow of the engine does not change greatly in the mode conversion process, the master control object selects the physical rotating speed of the low-pressure shaft of the engine, and the control rule of the master control object is set to keep the physical rotating speed of the low-pressure shaft unchanged. Besides the working condition parameters and the control law, constraint conditions which need to be met by the engine performance in the mode conversion process need to be input so as to test whether the mode conversion control law obtained by the method meets the design requirements or not. Constraints include, but are not limited to: the rotating speed is lower than the upper limit, the temperature of the gas at the important section is lower than the upper limit, the surge margin of the part is higher than the upper limit, the thrust has no step, the flow change range is small, and the like.
The working condition selected in the mode conversion process is an ultrasonic cruise point of the adaptive cycle aircraft engine, and the working condition parameter is (11km,1.5 Ma); the main control rule of the engine selectively controls the relative physical rotating speed of the low-pressure shaft to be 100 percent so as to ensure that the inlet flow of the engine is basically unchanged; the control law of the adjustable components at the start and end points of the mode transition is shown in table 3.
TABLE 3 Adjustable component control laws for Start and end points of mode transitions
Adjustable component VG1 VG2 VG3 VG4 VG5 VG6
Starting point -10° -10° 0 0.25 1.05 0.80
End point -30° -20° 1 1.00 1.00 1.00
The performance parameters for the adaptive cycle aircraft engine mode transition start and end points under the adjustable component control law conditions shown in table 3 are shown in table 4. Wherein, SMFANRepresenting fan surge margin, SMCDFSRepresenting core-driven fan surge margin, SMHPCRepresenting the surge margin of the high-pressure compressor, Nc,rel-FANRepresenting the relative converted speed of the fan, Nc,rel-CDFSRepresenting relative scaling of core-driven fansRotational speed, Nc,rel-HPCRepresenting the relative converted speed of the high pressure compressor.
TABLE 4 Engine Performance at Start and end points of mode transition
Performance parameter Frel wa,rel T4,rel SMFAN SMCDFS
Starting point 1.000 1.0000 0.9347 24.44％ 29.10％
End point 0.7817 1.0005 0.8525 35.23％ 26.35％
Performance parameter SMHPC Nc,rel-FAN Nc,rel-CDFS Nc,rel-HPC
Starting point 27.38％ 95.7％ 97.4％ 96.9％
End point 41.58％ 95.7％ 99.1％ 99.1％
S2: and checking whether the performance of the working conditions of the starting point and the ending point of the mode conversion of the engine meets the constraint condition.
The surge margin of the three compression parts is more than 10%, the rotating speed is lower than the maximum rotating speed limit value, the front temperature of the high-pressure turbine is lower than the maximum temperature limit, and the inlet flow of the engine has no obvious change. Since the mode transition starting point and the mode transition ending point are not two immediately adjacent working conditions, the constraint condition that the thrust step is less than 2% does not need to be satisfied. In summary, the engine performance under the starting point and the ending point of the mode conversion meets the constraint condition, and the process proceeds to step S3 to design the control law of the critical point before the mode conversion.
S3: and designing a control rule of the critical point before mode conversion by using a particle swarm optimization algorithm. The optimization goal is to reduce the thrust difference between the critical point before mode switching and the mode switching termination point, while the constraint condition of the mode switching process needs to be satisfied. By reducing the thrust difference between the critical point before mode conversion and the mode conversion termination point, the change of the thrust at the instant of state switching of the mode conversion valve is reduced as much as possible, so that the mode conversion is ensured to be carried out stably.
In the particle swarm optimization, the position of each particle represents the value of the adjustable component, and the speed of the particle represents the variation of the adjustable component. In the optimization, the value of the adjustable component is normalized, taking a core machine to drive the fan guide vane as an example, a normalization calculation formula is introduced, as shown in formula (15):
Figure BDA0002666389500000121
wherein VG1,0For the current core driving fan vane angle, VG1,minFor the minimum value of the angle of the fan guide vane, VG, driven by the core machine1,maxThe maximum value of the guide vane angle of the driving fan of the core machine.
At the critical point before the mode transition, the mode select valve is in an open state and not used as an optimization variable. The other 5 adjustable components in table 1 are used as optimization objects of the control law, and the positions of the particles in the particle swarm optimization can be expressed as formula (16):
Figure BDA0002666389500000122
in the particle swarm optimization, each particle has a fitness value reflecting the position of the particle. In the present embodiment, the fitness function is constructed with the goal of reducing the difference in thrust between the pre-mode-transition critical point and the mode transition termination point, while taking into account the constraints of speed, temperature, surge margin. The fitness function is shown as equation (17):
Figure BDA0002666389500000123
wherein, SMlimFor the minimum value limit of the surge margin, 10% is taken in the embodiment; t is4,maxFor the maximum limit of the total temperature of the inlet of the high-pressure turbine, 2150K is taken in the embodiment; n is a radical ofc,rel-maxRepresenting the maximum limit of the converted rotating speed, and taking 105% in the embodiment; μ represents a penalty function weight coefficient, which is 0.1 in this example. In the equation (17), different fitness functions can be formulated according to different choices of the constraint conditions, the value of the multiplication coefficient μ of the penalty function can be modified, and other types of penalty functions can be adopted.
The flow of the control law optimization algorithm based on the particle swarm optimization is shown in figure 4, and the specific steps are as follows:
s3-1: the initial positions and initial velocities of randomly generated m (20 in this embodiment) particles are shown in equations (18) and (19):
Figure BDA0002666389500000131
Figure BDA0002666389500000132
wherein the content of the first and second substances,
Figure BDA0002666389500000133
representing the normalized value change rate of the adjustable component; i represents the ith particle; j represents the jth iteration;
Figure BDA0002666389500000134
for the initial position of the jth iteration of the ith particle,
Figure BDA0002666389500000135
respectively taking the normalized values of the 1 st, 2 nd, 4 th, 5 th and 6 th adjustable components of the ith particle of the jth iteration,
Figure BDA0002666389500000136
for the initial velocity of the ith particle for the jth iteration,
Figure BDA0002666389500000137
respectively normalizing the value change rates of the 1 st, 2 nd, 4 th, 5 th and 6 th adjustable parts of the ith particle in the jth iteration;
s3-2: calculating the fitness of the current particle by using the formula (17), and further obtaining the position of the optimal point experienced by each particle
Figure BDA0002666389500000138
And the location of the optimum point experienced by the entire population
Figure BDA0002666389500000139
The particle fitness is a parameter reflecting the quality of the particle position, and the calculation method of the particle fitness comprehensively considers an optimization target and constraint conditions. The optimization target is to reduce the difference between a mode conversion front critical point and a mode conversion termination point, and a target function can be constructed by reducing the thrust difference of two working conditions, the value difference of an adjustable component and the like; the constraint conditions generally comprise that the rotating speed does not exceed a limit value, the temperature of the gas with an important section does not exceed the limit value, the surge margin of the part is higher than the minimum requirement and the like, and the constraint conditions can be reflected by using an internal penalty function.
S3-3: checking the best point experienced by the current population
Figure BDA00026663895000001310
Whether the optimization requirements are met or not, if so, according to the optimal point
Figure BDA00026663895000001311
Calculating to obtain an adjustable component control rule of a critical point before mode conversion; if the particle searching speed does not meet the requirement and the iteration number does not exceed the upper limit, the step S3-4 is carried out to update the particle searching speed;
s3-4: the search speed of the current generation particle is calculated using equation (20),
Figure BDA00026663895000001312
Figure BDA00026663895000001313
wherein, c1,c2The value range of the acceleration factor is generally [0,4 ]]In this example, 1.5 is taken; r is1,r2Is [0,1 ]]A random number within a range; w is a(j)Representing the dynamic inertia factor, winiFor the initial value of the inertia factor, 0.9 is taken in the embodiment; w is aendFor the inertia factor end value, 0.4 is taken in the present embodiment; j is a function ofmaxRepresenting the upper limit of the iteration algebra, the embodiment takes 200.
Acceleration factor c1,c2Other values may be taken within the usual ranges; the dynamic inertia factor of equation (21), and other forms of inertia factor expressions may be selected, such as: linearly decreasing the inertia factor, etc.
S3-5: after the particle searching speed is updated, the position of the next generation of particles is obtained by updating according to the formula (22), and then the step S3-2 is carried out to carry out a new iteration;
Figure BDA0002666389500000141
the control rule of the adjustable part of the critical point before mode conversion obtained by particle swarm optimization is shown in table 5, the performance parameters of the engine are shown in table 6, and the constraint conditions of temperature, rotating speed and surge margin are met.
TABLE 5 control law of critical points before mode transition
Adjustable partPiece VG1 VG2 VG3 VG4 VG5 VG6
Value taking -20° -10° 0 0.25 1.025 0.90
TABLE 6 Engine Performance at Critical Point before mode transition
Performance parameter Frel wa,rel T4,rel SMFAN SMCDFS
Value taking 0.8701 0.9952 0.8770 16.60％ 52.98％
Performance parameter SMHPC Nc,rel-FAN Nc,rel-CDFS Nc,rel-HPC
Value taking 32.49％ 95.7％ 96.7％ 98.7％
S4: and switching the on-off state of the mode switching valve, keeping the other adjustable components unchanged, and checking whether the performance of the engine meets the constraint.
Engine performance calculated by switching only the mode select valve from the closed state to the open state is shown in table 7. It can be seen that, the surge margins of the fan and the core engine driven fan do not satisfy the constraint condition, step S5 is performed, and the control rule of the critical point after the mode conversion is solved by using the sensitivity analysis.
TABLE 7 Engine Performance at Critical Point after mode transition (switching mode selector valve only)
Figure BDA0002666389500000142
Figure BDA0002666389500000151
S5: and solving the control rule of the critical point after the mode conversion by using sensitivity analysis. And developing sensitivity analysis aiming at the unsatisfied constraint condition of the mode conversion process, analyzing the influence of the adjustment of the adjustable component on the constraint condition, and preferentially adjusting the adjustable component with larger influence until the constraint condition of the mode conversion process is met, namely obtaining the control rule of the critical point after the mode conversion. By means of the sensitivity analysis method, mode conversion can be achieved smoothly with as few component adjustments as possible, and complexity of control system design is reduced.
The algorithm flow for solving the control law of the critical point after the mode conversion by using the sensitivity analysis is shown in fig. 5. And developing sensitivity analysis aiming at the unsatisfied mode conversion process constraint condition, and calculating the sensitivity of the unsatisfied constraint condition to the adjustable component. Taking the sensitivity of the fan surge margin to the angle of the guide vane of the core machine driving fan as an example, a sensitivity calculation method is introduced, as shown in formula (23):
Figure BDA0002666389500000152
wherein, SMFAN,0Representing fan surge margin after adjustment of guide vane angle, SMFAN,oriRepresenting the fan surge margin before adjusting the guide vane angle,
Figure BDA0002666389500000153
and representing the guide vane angle normalization adjustment quantity.
And the influence of the adjustment of each adjustable component on the constraint is obtained through sensitivity analysis. Selecting an adjustable component with the largest influence on the constraint, and solving the control law of the adjustable component by using a dichotomy:
s5-1: adjusting the adjustable component according to a given step length until a constraint condition is met for the first time, and obtaining an interval consisting of a current adjustable component value and an adjustable component previous point value, which are marked as [ a, b ];
s5-2: if the constraint is satisfied when the value of the adjustable component is a, turning to step S5-3; otherwise, go to step S5-4;
s5-3: and setting the value of the adjustable component as (a + b)/2, and substituting the value into the engine component-level simulation model to solve the engine performance. If the engine performance satisfies the constraint, setting a to (a + b)/2 to obtain a new interval [ a, b ], and proceeding to step S5-5; if the engine performance does not satisfy the constraint, setting b to (a + b)/2 to obtain a new interval [ a, b ], and proceeding to step S5-5;
s5-4: and setting the value of the adjustable component as (a + b)/2, and substituting the value into the engine component-level simulation model to solve the engine performance. If the engine performance satisfies the constraint, setting b to (a + b)/2 to obtain a new interval [ a, b ], and proceeding to step S5-5; if the engine performance does not satisfy the constraint, setting a to (a + b)/2 to obtain a new interval [ a, b ], and proceeding to step S5-5;
s5-5: and checking whether the width of the new interval [ a, b ] meets the requirement of iteration precision. If the accuracy is met, the step S5-6 is carried out, and the control rule of the critical point after the mode conversion is output; if the precision requirement is not met, the step S5-2 is carried out to continue iteration;
s5-6: if the constraint is satisfied when the value of the adjustable component is a, taking the value of a as a control rule of the critical point after mode conversion; otherwise, the value of b is used as the control rule of the critical point after the mode conversion.
When all the constraint conditions are satisfied, the control rule of the critical point after the mode conversion can be obtained. The engine performance at the mode switching pre/post critical point in this embodiment is summarized in table 8.
TABLE 8 Engine Performance before and after mode transition Critical points
Performance of Frel wa,rel T4,rel SMFAN SMCDFS
Front critical point 0.8701 0.9952 0.8770 16.60％ 52.98％
Rear critical point 0.8825 0.9876 0.8878 11.03％ 10.05％
Performance of SMHPC Nc,rel-FAN Nc,rel-CDFS Nc,rel-HPC
Front critical point 32.49％ 95.7％ 96.7％ 98.7％
Rear critical point 22.46％ 95.7％ 92.7％ 91.8％
It can be seen that the critical point after the mode conversion meets the constraint conditions of temperature, rotating speed and surge margin; meanwhile, the constraint conditions that the flow change is not more than 2% and the thrust step is not more than 2% are met. Thus, the current adjustable component control law satisfies all constraints of the mode transition. The control law of the current adjustable component is shown in table 9.
TABLE 9 control law of critical points after mode transition
Adjustable component VG1 VG2 VG3 VG4 VG5 VG6
Value taking -20.3° -10° 0 0.402 1.025 0.90
S6: and obtaining the control rules of the adjustment stage before mode conversion and the adjustment stage after mode conversion by utilizing linear interpolation.
Based on the obtained critical point control rule before mode conversion and the mode conversion initial point control rule, the control rule of the adjustment stage before mode conversion is obtained by utilizing linear interpolation; and obtaining a control rule of an adjustment stage after mode conversion by utilizing linear interpolation based on the obtained control rule of the critical point after mode conversion and the control rule of the mode conversion termination point. In the process of solving the control law of the pre-adjustment stage and the post-adjustment stage of the mode conversion by using the linear interpolation, if the constraint condition of the mode conversion process is not satisfied, finding the adjustable component with the largest influence on the constraint adjustment by using a sensitivity analysis method, preferentially adjusting the adjustable component until the constraint condition is satisfied, and finally realizing the stable operation of the mode conversion process.
The linear interpolation needs to preset the number of interpolation points, the interpolation step length is calculated by using the formula (24), and the adjustable component value of each interpolation point is obtained by using the formula (25).
Figure BDA0002666389500000161
Figure BDA0002666389500000162
Wherein Δ VGkRepresents the interpolation step of the kth adjustable component, k is 1,2, … n, VGk,startRepresenting the value of the interpolation starting point of the kth adjustable component, VGk,endRepresenting the value of an interpolation termination point of the kth adjustable component, and num represents the number of the interpolation points; VG(q)The value of the adjustable component representing the qth interpolation point; VG1,startThe value of the interpolation starting point of the 1 st adjustable component is represented, and delta VG1Represents the interpolation step length of the 1 st adjustable component; VG2,startThe value of the interpolation starting point, Δ VG, representing the 2 nd tunable component2Represents the interpolation step size of the 2 nd adjustable component; VG6,startThe value of the interpolation starting point of the 6 th adjustable component is represented, and delta VG6Representing the interpolation step size for the 6 th adjustable component.
In this embodiment, 50 interpolation points are selected, that is, 50 working conditions are experienced from the mode conversion starting point to the mode conversion front critical point, and 50 working conditions are experienced from the mode conversion rear critical point to the mode conversion end point.
In the process of solving the control rules of the pre-mode conversion adjustment stage and the post-mode conversion adjustment stage by using the linear interpolation, if the constraint conditions of the mode conversion process are not satisfied, the same method as that in the step S5 is used, the adjustable component most affecting the constraint adjustment is found by using the sensitivity analysis method, the adjustable component is preferentially adjusted, the control rules of the adjustable component are solved by using the dichotomy until all the constraint conditions are satisfied, and finally the mode conversion process is stably performed.
S7: and outputting a control rule design result of the mode conversion process.
The results of designing the control law in the mode switching process are shown in fig. 6 and 7, and the changes in the engine performance during the mode switching process are shown in fig. 8, 9, and 10.
After the control rules and the working condition parameters of the starting point and the ending point of the mode conversion are given, the method can quickly finish the automatic design of the control rules in the mode conversion process by using a program, and avoids the fussy and low efficiency of manual regulation.
The embodiment is described based on one adaptive cycle aircraft engine configuration, but the method of the invention is applicable to adaptive cycle aircraft engines with various configurations. The invention relates to an automatic design method for a mode conversion process control rule of a self-adaptive circulation aircraft engine. The first innovation is to simplify the design process of the whole mode conversion process into the design of two key working conditions, namely: the two working conditions before and after the mode selection valve is switched on/off are reasonably designed through a control rule to ensure that the mode switching is stably carried out; the second innovation is that a control rule is designed by using a particle swarm optimization and sensitivity analysis method, and the optimization design can be automatically carried out only by setting the control rule and working condition parameters of a mode conversion starting point and a mode conversion ending point, so that the complexity caused by manual adjustment is avoided; the third innovation is that the design method has universality. The input parameters of the method are working condition parameters and control rules of the starting point and the ending point of the mode conversion. When the design parameters or the component characteristics are changed, the input parameters are not required to be changed, and the control rule design can be still rapidly completed by using the method.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (6)

1. A method for designing a control law of a mode conversion process of a self-adaptive circulation aero-engine is characterized in that,
the mode conversion process is simplified into two important working conditions: the mode selection valve state is a critical point before mode conversion before switching, and the mode selection valve state is a critical point after mode conversion after switching;
the two important working conditions divide the mode conversion process into three stages, namely a stage of adjusting before mode conversion from a mode conversion starting point to a mode conversion front critical point, a stage of adjusting before mode conversion from the mode conversion front critical point to a mode conversion rear critical point, a stage of adjusting after mode conversion from the mode conversion rear critical point to the mode conversion end point,
specifically, the design method comprises the following steps:
s1: setting working condition parameters and control rules of a mode conversion starting point and an end point of the self-adaptive cycle aero-engine, inputting the working condition parameters and the control rules into an engine component level performance simulation model for calculation, and obtaining the performance of the starting point and the end point of the engine; given constraint conditions which need to be met by the engine performance in the mode conversion process;
s2: it is checked whether the performances of the start point and the end point of the engine mode transition obtained in step S1 satisfy the constraints of the mode transition process: if the constraint condition is not met, outputting a prompt that the working condition and/or the control rule of the mode conversion starting point and/or the mode conversion ending point need to be changed, and ending the design process; if the constraint condition is met, the step S3 is carried out to design the control rule of the critical point before the mode conversion;
s3: the design of a control rule of a critical point adjustable component before mode conversion is carried out by utilizing a particle swarm optimization algorithm, the optimization aim is to reduce the difference between the critical point before mode conversion and a mode conversion termination point, reduce the change of the thrust at the moment of state switching of a mode conversion valve so as to ensure that the mode conversion is carried out stably, and simultaneously meet the constraint condition of the mode conversion process;
s4: switching the on-off state of the mode conversion valve, calculating the performance of the engine, and checking whether the performance of the engine meets the constraint condition of the mode conversion process: if the condition is met, obtaining a control rule of the critical point after the mode conversion, and turning to step S6 to design the control rule of the pre-mode conversion adjusting stage and the post-mode conversion adjusting stage; if not, the process goes to step S5;
s5: solving a control rule of the critical point after the mode conversion by using sensitivity analysis, developing sensitivity analysis aiming at the constraint condition of the unsatisfied mode conversion process, analyzing the influence of the adjustment of the adjustable component on the constraint condition, and sequentially adjusting the adjustable component according to the influence degree until the constraint condition of the mode conversion process is satisfied, namely obtaining the control rule of the critical point after the mode conversion;
s6: based on the critical point control rule before mode conversion obtained in step S3 in combination with the mode conversion starting point control rule, a control rule of the adjustment stage before mode conversion is obtained by using linear interpolation; based on the control law of the critical point after the mode conversion obtained in the step S4 or the step S5 and the control law of the mode conversion termination point, the control law of the adjustment stage after the mode conversion is obtained by utilizing linear interpolation;
s7: and outputting a control rule design result of the mode conversion process.
2. The method for designing the mode transition process control law of the adaptive-cycle aircraft engine according to claim 1, wherein the method of the step S3 is as follows:
s3-1: initial positions, initial velocities and normalized definitions of m particles are randomly generated as shown in equations (1), (2) and (3), respectively:
Figure FDA0002666389490000021
Figure FDA0002666389490000022
Figure FDA0002666389490000023
wherein i represents the ith particle; j represents the jth iteration;
Figure FDA0002666389490000024
for the position of the jth iteration of the ith particle,
Figure FDA0002666389490000025
represents the normalized value of the nth tunable component,
Figure FDA0002666389490000026
is the jth turnThe normalized value of the 1 st adjustable component which replaces the ith particle,
Figure FDA0002666389490000027
for the normalized value of the 2 nd adjustable component of the ith particle of the jth iteration,
Figure FDA0002666389490000028
normalizing the value of the nth adjustable component of the ith particle in the jth iteration; vi (j)For the speed of the jth iteration of the ith particle,
Figure FDA0002666389490000029
representing the normalized rate of change of value of the nth tunable component,
Figure FDA00026663894900000210
the normalized rate of change of value of the 1 st adjustable component for the ith particle of the jth iteration,
Figure FDA00026663894900000211
the normalized rate of change of value of the 2 nd adjustable component for the ith particle of the jth iteration,
Figure FDA00026663894900000212
normalized variation rate of value, VG, of the nth tunable element for the ith particle of the jth iterationn,0Representing the current value of the nth adjustable component, VGn,minRepresenting the lower limit of the value of the nth adjustable component, VGn,maxRepresents the upper limit of the value of the nth adjustable component;
s3-2: calculating the particle fitness; constructing a fitness function by linear weighting and comprehensively considering an optimization target and a constraint condition
Figure FDA00026663894900000213
Figure FDA00026663894900000214
Wherein: tag represents the optimized target value, PF1Represents the value of the 1 st penalty function, PF2Represents the value of the 2 nd penalty function, PFtRepresents the value of the t-th penalty function, w1Weight coefficient, w, representing the 1 st penalty function2Weight coefficient, w, representing the 2 nd penalty functiontA weighting factor representing the tth penalty function;
s3-3: after the fitness of the current particle is calculated in the step S3-2, the position of the optimal point experienced by the particle is obtained
Figure FDA00026663894900000215
And the location of the optimum point experienced by the entire population
Figure FDA00026663894900000216
Checking the best point experienced by the current population
Figure FDA00026663894900000217
Whether the optimization requirements are met or not, if so, according to the optimal point
Figure FDA00026663894900000218
Calculating to obtain an adjustable component control rule of a critical point before mode conversion; if the particle searching speed does not meet the requirement and the iteration number does not exceed the upper limit, the step S3-4 is carried out to update the particle searching speed;
s3-4: the search speed of the particle is updated using equation (5):
Figure FDA00026663894900000219
wherein, Vi (j+1)The speed of the j +1 th iteration of the ith particle; c. C1,c2Is an acceleration factor with a value range of [0,4 ]]；r1,r2Is [0,1 ]]A random number within a range; w is a(j)Representing dynamic inertia factor, the value is (0,1),can take a fixed value or a dynamic value;
s3-5: updating according to the formula (6) to obtain the position of the next generation of particles, and then turning to the step S3-2 to perform a new iteration;
Figure FDA0002666389490000031
wherein the content of the first and second substances,
Figure FDA0002666389490000032
is the position of the j +1 th iteration of the ith particle.
3. The method for designing the mode transition process control law of the adaptive-cycle aircraft engine according to claim 1 or 2, wherein the specific process of the step S5 is as follows:
the sensitivity analysis is evaluated by calculating function variation caused by unit variation of the variable, and the sensitivity analysis of the constraint condition on the adjustable component is calculated as shown in the formula (7):
Figure FDA0002666389490000033
wherein Senr,sRepresenting sensitivity of the r-th constraint to the s-th adjustable component, Resr,0Representing the value of the r-th constraint condition, Res, after the adjustment of the s-th adjustable elementr,oriRepresenting the value of the r-th constraint condition before the adjustment of the s-th adjustable component,
Figure FDA0002666389490000034
represents the normalized adjustment of the s-th adjustable component;
after the adjustable component is selected by sensitivity analysis, the value of the adjustable component is obtained by utilizing a dichotomy, and the method comprises the following specific steps:
s5-1: adjusting the adjustable component according to a given step length until a mode conversion process constraint condition is met for the first time, and obtaining an interval consisting of a current adjustable component value and an adjustable component previous point value, and recording the interval as [ a, b ];
s5-2: if the value of the adjustable component is a, the constraint condition is met, and the step is switched to the step S5-3; otherwise, go to step S5-4;
s5-3: setting the value of the adjustable component as (a + b)/2, substituting the value into an engine component-level simulation model to solve the engine performance;
if the engine performance satisfies the constraint condition, setting a to (a + b)/2 to obtain a new interval [ a, b ], and going to step S5-5;
if the engine performance does not satisfy the constraint condition, setting b to (a + b)/2 to obtain a new interval [ a, b ], and going to step S5-5;
s5-4: setting the value of the adjustable component as (a + b)/2, substituting the value into an engine component-level simulation model to solve the engine performance;
if the engine performance satisfies the constraint condition, setting b to (a + b)/2 to obtain a new interval [ a, b ], and going to step S5-5;
if the engine performance does not satisfy the constraint condition, setting a to (a + b)/2 to obtain a new interval [ a, b ], and going to step S5-5;
s5-5: checking whether the width of the new interval [ a, b ] meets the requirement of iteration precision;
if the accuracy is met, the step S5-6 is carried out, and the control rule of the critical point after the mode conversion is output;
if the accuracy requirement is not met, the step S5-2 is carried out to continue iteration;
s5-6: when the value of the adjustable component is a, the constraint condition is met, and the value of a is taken as the value of the critical point of the adjustable component after mode conversion; otherwise, taking the value of b as the value of the critical point of the adjustable component after mode conversion; when all the constraint conditions are met, the control rule of the critical point after the mode conversion is obtained.
4. The method for designing the mode transition process control law of the adaptive-cycle aircraft engine according to claim 1 or 2, wherein the specific process of the step S6 is as follows:
presetting interpolation points, calculating interpolation step length by using a formula (8), and obtaining the value of an adjustable component of the interpolation point by using a formula (9);
Figure FDA0002666389490000041
Figure FDA0002666389490000042
wherein Δ VGkRepresents the interpolation step of the kth adjustable component, k is 1,2, … n; VGk,startRepresenting the value of the interpolation starting point of the kth adjustable component, VGk,endRepresenting the value of an interpolation termination point of the kth adjustable component, and num represents the number of the interpolation points; VG(q)The value of the adjustable component representing the qth interpolation point; in particular VG1,startThe value of the interpolation starting point of the 1 st adjustable component is represented, and delta VG1Represents the interpolation step length of the 1 st adjustable component; VG2,startThe value of the interpolation starting point, Δ VG, representing the 2 nd tunable component2Represents the interpolation step size of the 2 nd adjustable component; VGn,startRepresenting the value of the interpolation starting point of the nth adjustable component, Δ VGnRepresents the interpolation step length of the nth adjustable component;
in the process of solving the control law of the pre-adjustment stage and the post-adjustment stage of the mode conversion by using the linear interpolation, when the constraint condition of the mode conversion process is not met, the method which is the same as the design of the control law of the post-mode conversion critical point is adopted: firstly, finding out an adjustable component with the largest influence on the constraint adjustment of the mode conversion process through a sensitivity analysis method, preferentially adjusting the adjustable component, solving the control rule of the adjustable component by utilizing a dichotomy until all constraint conditions are met, and finally realizing the stable operation of the mode conversion process.
5. The method for designing the control law of the mode conversion process of the adaptive-cycle aircraft engine as claimed in claim 1, wherein in step S1, the main control object is selected as the low-pressure shaft physical rotation speed in the component-level simulation model, and the control law is set to ensure that the low-pressure shaft physical rotation speed is not changed.
6. The method for designing a mode transition process control law of an adaptive-cycle aircraft engine according to one of claims 1 to 6, wherein in the step S1, the constraint conditions to be met by the engine performance during the mode transition process include that the rotating speed is lower than a set upper limit, the temperature of the important section gas is lower than the set upper limit, the surge margin of the component is higher than the set upper limit, the thrust step is lower than the set upper limit and the flow change range is lower than the set upper limit.
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