Vce cross-mode control method considering thrust rapid response and fuel economy

Abstract

The application belongs to the technical field of aero-engine control, and specifically discloses a VCE cross-mode control method which takes into account thrust rapid response and fuel economy, comprising the following steps: screening feasible steady points offline, and constructing a thrust-economy fuel guide mapping; calculating a reliability factor online according to the thrust-economy fuel guide mapping; obtaining a local linear prediction model according to current scheduling variable sampling, and constructing an output prediction matrix in a prediction time domain; constructing a model predictive control cost function and a hard constraint condition, and then solving a quadratic programming problem to obtain a control increment sequence, and applying the first control increment to the engine to output control instructions of fuel flow, a mode switching factor and a nozzle area. The application solves the problems that in the VCE thrust transition state or mode switching task, a fixed terminal target of BETA_MSV and A8 must be preset through performance optimization method, and direct fuel square punishment leads to the problem that fuel unconditionally tends to the lower limit.

Description

Technical Field

[0001] This invention belongs to the field of aero-engine control technology, specifically relating to a VCE cross-modal control method that balances rapid thrust response and fuel economy. Background Technology

[0002] Variable cycle (VCE) aero-engines can alter internal flow path matching and cycle parameters through variable geometry mechanisms, enabling the engine to operate with different characteristics under varying flight missions and thrust requirements. Compared to fixed cycle engines, VCE engines exhibit stronger coupling between actuated variables such as fuel flow rate, mode switching mechanism, and nozzle area. Changes in these variables not only affect thrust response but also turbine temperature, compressor stability margin, and fuel consumption. Therefore, VCE engine control problems typically manifest as multivariable, strongly constrained collaborative control problems.

[0003] The mode switching process is a crucial step for variable cycle engines to switch between different operating states. During this process, the mode switching mechanism, nozzle area, and fuel flow rate need to change in tandem; otherwise, thrust fluctuations, component mismatches, temperature increases, or reduced surge margins may occur. Therefore, the mode switching process not only requires the actuators to complete position transitions but also demands that the engine maintain thrust stability and safety constraints throughout the entire transition.

[0004] Existing mode-switching control methods typically treat the mode-switching process as a transition between endpoint modes. They pre-set the adjustment trajectories of the mode-switching mechanism, nozzle area, or other variable geometries, and then use open-loop optimization, closed-loop control, or predictive control to reduce thrust fluctuations and maintain safety boundaries. While these methods can improve mode-switching smoothness, given a specific thrust mission, the controller usually still needs to track a predetermined geometric trajectory or endpoint configuration, limiting the ability for free and coordinated optimization of geometric variables.

[0005] Furthermore, fuel economy is a crucial objective in aero-engine control. However, directly incorporating the fuel flow square term (WFM²) into the control cost function, which expresses "the less fuel, the better," can easily conflict with thrust response objectives. For variable-cycle engines, a more reasonable economic control objective should be to achieve fuel flow rates close to the economic fuel guidance that matches the current thrust mission, while satisfying current thrust requirements, temperature constraints, and surge margin constraints. Therefore, it is necessary to construct a thrust-oriented economic fuel guidance mapping and integrate it with multi-actuator cooperative predictive control for variable-cycle engines.

[0006] In summary, the existing technology mainly has the following problems: (1) The preset geometric terminal target limits the utilization of the VCE intermediate configuration. In existing mode switching control, The A8 is often required to reach a certain endpoint mode or preset terminal position within a specified time, which means that the controller can only execute the manually specified geometry switching path, making it difficult to autonomously select a more advantageous intermediate configuration based on current thrust requirements, fuel consumption and safety constraints.

[0007] (2) Directly using WFM² as a fuel penalty term lacks sufficient physical meaning. The WFM² cost essentially expresses "the lower the fuel, the better," and the optimizer tends to make the fuel flow (WFM) close to the lower limit. For engines that need to generate thrust, the fuel is not necessarily better the lower it is, but should be kept at a reasonable level while meeting thrust requirements, temperature constraints, and surge margin constraints.

[0008] (3) Lack of an economic fuel guidance generation mechanism for thrust missions. Traditional MPC can handle constraints and tracking, but if it does not construct an economic fuel guidance (WFM_eco) based on the thrust target and the feasible steady-state point, the fuel economy item is out of touch with mission requirements, making it difficult to explain whether the fuel level selected by the controller is "economical" or merely "too low".

[0009] (4) The reliability of economic reference under low-density LPV steady-state grid is not evaluated. The number of LPV steady-state grids of VCE is usually limited. If the thrust-fuel mapping is directly established based on sparse steady-state points, there may be insufficient support points in some thrust regions, resulting in insufficient reliability of WFM_eco interpolation results.

[0010] (5) Intermediate mode dwelling behavior lacks interpretable control logic. If the controller remains in the intermediate mode switching state for a long time, existing methods may regard it as an incomplete switching or a lingering state, rather than a dwellable intermediate cycle working state formed under the combined effect of thrust, economy and safety constraints. Summary of the Invention

[0011] The purpose of this invention is to address the challenges of how to determine the coordinated adjustment path of fuel flow rate, mode switching factor, and nozzle area by the controller based on thrust mission, fuel economy guidance, temperature constraints, and surge margin constraints during VCE thrust transition or mode switching tasks, without pre-setting fixed end targets for BETA_MSV and A8 through performance optimization methods. Simultaneously, it aims to avoid the direct fuel square penalty causing fuel to unconditionally approach the lower limit, and to evaluate the reliability of fuel economy guidance when the LPV steady-state grid density is finite. Therefore, this invention proposes a VCE cross-modal control method that balances rapid thrust response and fuel economy.

[0012] The technical solution of this invention is: a VCE cross-modal control method that balances rapid thrust response and fuel economy, comprising the following steps: A linear variable parameter steady-state operating condition grid for a variable cycle aero-engine was established offline, and the steady-state points in the linear variable parameter steady-state operating condition grid were screened for safety feasibility to obtain feasible steady-state points. Construct a thrust-economic fuel guide mapping based on a feasible steady-state point; Obtain the current thrust reference online, obtain the current economic fuel guidance value based on the thrust-economic fuel guidance mapping, and calculate the confidence factor; Based on the current scheduling variables, a local linear prediction model is obtained by sampling from the linear variable parameter steady-state operating condition grid, and the output prediction matrix in the prediction time domain is constructed. Construct a model to predict the control cost function based on the output prediction matrix and the confidence factor; Hard constraints are constructed based on the output prediction matrix, including temperature constraints, surge margin constraints, actuator amplitude constraints, and actuator rate constraints. Solve the quadratic programming problem of the model predictive control cost function under hard constraints to obtain the control increment sequence. Apply the first control increment to the engine to output control commands for fuel flow, mode switching factor and nozzle area, thus completing VCE cross-modal control.

[0013] As a preferred option, the screening criteria for safety feasibility screening of steady-state points in the linear variable parameter steady-state grid include:

[0014] in, Indicates fuel flow rate. Indicates turbine temperature, Indicates engine thrust. Indicates the fan surge margin. Indicates the surge margin of a medium-pressure compressor. Indicates the surge margin of the high-pressure compressor. This indicates the maximum permissible value for turbine temperature. This represents the minimum allowable value for fan surge margin. This represents the minimum allowable surge margin for a medium-pressure compressor. This indicates the minimum allowable surge margin of a high-pressure compressor.

[0015] As a preferred option, the method for constructing a thrust-fuel-economical guidance mapping based on a feasible steady-state point is as follows: For a given thrust target, determine the set of steady-state points that satisfy the thrust difference threshold among feasible steady-state points. :

[0016] in, Indicates the first The net engine thrust corresponding to a feasible steady-state point Indicates the thrust neighborhood threshold. Represents the set of feasible steady-state points; Select the steady-state point with the minimum fuel flow rate from the set of steady-state points as the economical fuel guide for a given thrust target:

[0017] in, Indicates a given thrust target Corresponding fuel economy guidelines Represents the set of steady-state points The selection is based on the principle of minimizing fuel flow. Indicates the first The fuel flow rate corresponding to each feasible steady-state point; By selecting fuel-efficient guidance for multiple thrust targets, a thrust-fuel-efficient guidance mapping table is obtained:

[0018] in, Indicates the first The thrust support level of each engine Indicates the relationship with the first The fuel economy guidance corresponding to the thrust support level of each engine. This indicates the number of feasible steady-state support points in the thrust-economy fuel guidance mapping table.

[0019] Preferably, the confidence factor is determined by the number of feasible steady-state support points in the thrust neighborhood, the thrust distance between the thrust target and the nearest feasible steady-state point, and whether the thrust target is located within the thrust range covered by the feasible steady-state support points used to construct the WFMeco map. The specific formula is as follows:

[0020] in, This represents the reliability factor for economical fuel consumption at the current sampling time. Indicates the current thrust reference The number of feasible steady-state support points within the neighborhood; This indicates the minimum expected number of support points. This indicates the thrust distance between the current thrust reference and the nearest feasible steady-state support point; This indicates the preset maximum allowed nearest neighbor distance threshold; This indicates the range coverage flag, which is used when the current thrust reference is within the thrust range covered by the economic fuel guide mapping support point. ,otherwise ; Represents a saturation function; Number of feasible steady-state support points in the current thrust reference neighborhood Thrust distance to nearest neighbor They are represented as follows:

[0021] in, Indicates the first The engine thrust corresponding to a feasible steady-state support point This represents the thrust neighborhood threshold.

[0022] As a preferred option, the local linear prediction model is as follows:

[0023] in, This represents the state vector at the next sampling time. Indicates the scheduling variable A defined state matrix, This represents the state vector at the current sampling time. Represents the input matrix, This represents the current control input vector. Represents the steady-state bias or affine term. Indicates the output vector. Indicates the output matrix. Indicates direct transmission of the matrix. This indicates the output bias or affine term.

[0024] Preferably, the output prediction matrix is ​​used to map the future control increment sequence into output prediction values ​​of engine thrust, turbine temperature, fan surge margin, intermediate-pressure compressor surge margin, and high-pressure compressor surge margin in the prediction time domain.

[0025] As a preferred option, the model predictive control cost function Specifically:

[0026] in, For thrust tracking, Indicates the thrust tracking weight. This is a deviation item for economical fuel consumption. Indicates the weight of fuel economy. To control incremental penalty items, This represents the control increment weight matrix. Indicates the length of the prediction time domain. Indicates in The first time predicted Step engine net thrust, Indicates in Time of the first The corresponding thrust reference for each step Indicates in Time of the first Predicting fuel flow step by step, Indicates in Time of the first The fuel-efficient guide is derived from the thrust target mapping. Indicates in Time of the first Step control increment, superscript Indicates transpose. This indicates the length of the control time domain.

[0027] As a preferred option, the temperature constraint is: .

[0028] in, Indicates in The first time predicted Step turbine temperature, This indicates the maximum permissible value for turbine temperature; The surge margin constraint is:

[0029] in, Indicates in The first time predicted step fan surge margin, Indicates in The first time predicted Surge margin of the intermediate-pressure compressor. Indicates in The first time predicted High-pressure compressor surge margin, This represents the minimum allowable value for fan surge margin. This represents the minimum allowable surge margin for a medium-pressure compressor. This indicates the minimum allowable surge margin of a high-pressure compressor; The actuator amplitude constraint is:

[0030] in, This indicates the lower limit of the control input amplitude. This represents the control input vector predicted at time k for the i-th step. This indicates the upper limit of the control input amplitude; The actuator rate constraint is:

[0031] in, This indicates the lower limit of the control increment. This represents the i-th control increment predicted at time k. This indicates the upper limit of the control increment.

[0032] Preferably, the mode switching factor and nozzle area are not set with fixed terminal tracking targets. Instead, the mode switching factor and nozzle area are used as free collaborative optimization variables, so that the engine can stay and operate in the intermediate circulation region between the turbofan mode and the turbojet mode.

[0033] The beneficial effects of this invention are: This invention enables thrust mission tracking, fuel economy guidance, and safety constraint maintenance without forcing geometric variables to follow preset terminal values. It allows the VCE to reside in the intermediate circulation region between the turbofan and turbojet modes while meeting thrust, temperature, and surge margin constraints, thereby transforming the intermediate mode from a "transition segment that must be traversed as quickly as possible" into a "working region that can be selected and maintained by the optimizer." Attached Figure Description

[0034] Figure 1 The diagram shows a flowchart of a VCE cross-modal control method that balances rapid thrust response and fuel economy.

[0035] Figure 2 The figure shows the net thrust under two fuel cost functions. How it changes over time.

[0036] Figure 3 The figure shows the fuel flow rate under two fuel cost functions. How it changes over time.

[0037] Figure 4 The figure shows the low-pressure speed under two fuel cost functions. How it changes over time.

[0038] Figure 5 The figure shows the high-pressure speed under two fuel cost functions. How it changes over time.

[0039] Figure 6 The figure shows the mode switching factor under two fuel cost functions. How it changes over time.

[0040] Figure 7 The figure shows the nozzle area under two fuel cost functions. How it changes over time.

[0041] Figure 8 The figure shows the turbine temperature under two fuel cost functions. Solution time.

[0042] Figure 9 The figure shows the fan surge margin under two fuel cost functions. Solution time.

[0043] Figure 10 The figure shows the surge margin of the medium-pressure compressor under two fuel cost functions. Solution time.

[0044] Figure 11 The figure shows the QP solution time under two fuel cost functions.

[0045] Figure 12 The image shown is in Plot the feasible steady-state point of LPV, the selected fuel economy support point, and the data obtained by interpolation from the support point on the plane. curve.

[0046] Figure 13 The figures show the number of neighborhood steady-state points and the proportion of nearest neighbor distance to thrust range under different thrust support levels.

[0047] Figure 14 The image shows the APRBS thrust step command. Changes over time.

[0048] Figure 15 The figure shows the fuel economy reference obtained by online interpolation based on the thrust command. .

[0049] Figure 16 The figure shows the number of LPV steady-state support points near the thrust target for each APRBS segment.

[0050] Figure 17 The figure shows the proportion of the nearest neighbor distance to the thrust range for each APRBS segment. Detailed Implementation

[0051] Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the drawings are merely exemplary and are intended to illustrate the principles and spirit of the invention, and are not intended to limit the scope of the invention.

[0052] Terminology Explanation: BETA_MSV: Equivalent area of ​​the mode switching mechanism or mode switching factor.

[0053] A8: Nozzle area or nozzle area ratio.

[0054] Intermediate cycle dwell: The engine continues to operate in the intermediate configuration region between the turbofan-type end mode and the turbojet-type end mode.

[0055] LPV steady-state mesh: A collection of multi-condition steady-state data obtained from component-level models, simulations, or experiments.

[0056] Example 1: A VCE cross-modal control method that balances rapid thrust response and fuel economy comprises five levels: offline modeling and mapping construction, online reference generation, online predictive optimization, control command output, and reliability diagnosis. The controlled object of this method is a variable cycle aero-engine or its component-level model / LPV model, and the control variable... Defined as:

[0057] in, For fuel flow rate, The equivalent area or mode switching factor of the mode switching mechanism. The nozzle area or area ratio is indicated by the superscript. Indicates transpose. Output quantity Defined as:

[0058] in, For low-pressure speed, For high pressure and high speed, This refers to a quantity related to turbine temperature or turbine inlet temperature. For engine thrust, , , These are surge margins for fans, medium-pressure compressors, and high-pressure compressors, respectively.

[0059] like Figure 1 As shown, a VCE cross-modal control method that balances rapid thrust response and fuel economy includes the following steps: S1. Establish a linear variable parameter steady-state operating condition grid for the variable cycle aero-engine offline, and perform safety feasibility screening on the steady-state points in the linear variable parameter steady-state operating condition grid to obtain feasible steady-state points; S2. Construct a thrust-economic fuel guide mapping based on a feasible steady-state point; S3. Obtain the current thrust reference online, obtain the current economic fuel guidance value based on the thrust-economic fuel guidance mapping, and calculate the confidence factor; S4. Based on the current scheduling variables, sample the local linear prediction model from the linear variable parameter steady-state condition grid, and construct the output prediction matrix in the prediction time domain; S5. Construct a model to predict the control cost function based on the output prediction matrix and confidence factor; S6. Construct hard constraints based on the output prediction matrix, including temperature constraints, surge margin constraints, actuator amplitude constraints, and actuator rate constraints; S7. Solve the quadratic programming problem of the model predictive control cost function under hard constraints to obtain the control increment sequence. Apply the first control increment to the engine to output control commands for fuel flow, mode switching factor and nozzle area, thus completing VCE cross-modal control.

[0060] In this embodiment, step S1 specifically includes: During the offline phase, a steady-state mesh for the VCE's LPV is established. This mesh can be obtained from component-level models, experimental data, simulation data, or existing engine performance databases. Each steady-state point contains at least the control variables. Output and necessary scheduling amount .

[0061] For each steady-state point in the LPV steady-state grid, a safety feasibility screening is performed, and steady-state points that meet the following conditions are retained:

[0062] in, This indicates the maximum value of a quantity related to turbine temperature or turbine inlet temperature. This represents the minimum value of the fan surge margin. This represents the minimum surge margin of a medium-pressure compressor. This represents the minimum surge margin of the high-pressure compressor. The above screening ensures that the steady-state point used to construct the fuel economy guide does not violate temperature and surge margin constraints. If there are too few feasible points in some areas, the screening conditions can be relaxed for diagnostic purposes, but in actual control, the weight of the fuel economy term should be reduced or a conservative control strategy should be switched to that area.

[0063] In this embodiment, step S2 specifically includes: For a given thrust target To find the feasible steady-state point of LPV that satisfies safety constraints. Set of adjacent steady-state points :

[0064] in, Indicates the first The net engine thrust corresponding to a feasible steady-state point Indicates the thrust neighborhood threshold. This represents the set of feasible steady-state points that satisfy the screening conditions of temperature constraint, surge margin constraint, and positive fuel flow rate. Determined based on a fixed proportion of the full thrust range, a relative proportion of the current thrust target, or the larger of both. Then... The steady-state point with lower fuel flow rate is selected as the guide for economical fuel consumption.

[0065] in, Indicates a given thrust target Corresponding fuel economy guidelines Represents the set of steady-state points The selection is based on the principle of minimizing fuel flow. Indicates the first The fuel flow rate corresponding to each feasible steady-state point.

[0066] like If the value is empty, a protection strategy of nearest neighbor steady-state point or interpolation extrapolation is adopted, but the reliability flag of the reference should be output at the same time. Repeating the above operation for multiple thrust support points yields a discrete mapping table:

[0067] in, Indicates the first One thrust support level, Indicates the relationship with the first The economic fuel guidance corresponding to each thrust support level. This indicates the number of support points in the thrust-economy fuel steering mapping table. The support point range refers to the coverage area of ​​support points used for economy fuel steering mapping after safety and feasibility screening, not the entire range of unscreened steady-state points.

[0068] During online control, for the current thrust target Perform linear interpolation, piecewise cubic interpolation, nearest neighbor interpolation, or other one-dimensional / multi-dimensional interpolation to obtain the current economic fuel guide. If flight altitude is taken into account ,Mach number or scheduling quantity It can be expanded into a multidimensional mapping:

[0069] in, This represents a mapping function guided by inputs such as thrust target, flight altitude, Mach number, and scheduling variables to determine fuel economy.

[0070] In this embodiment, step S3 specifically includes: To avoid insufficient reliability of the fuel economy guidance reference due to low-density LPV steady-state grids, this invention performs online calculations. Simultaneously calculate the credibility factor This confidence factor is not obtained by fitting training samples, but rather constructed based on the steady-state grid support mass near the current thrust reference. Specifically, the current thrust reference is first statistically analyzed. Number of feasible steady-state support points in the neighborhood It also calculates the thrust distance between the current thrust reference and the nearest feasible steady-state support point. Then, determine whether the current thrust reference is within the thrust range covered by the economic fuel guide mapping support point to obtain the interval coverage flag. The credibility factor is defined as:

[0071] Specifically, when the current thrust reference is within the thrust range covered by the economic fuel guide mapping support point... ,otherwise ; The saturation function is defined as:

[0072] Number of feasible steady-state support points in the current thrust reference neighborhood Thrust distance to nearest neighbor They are represented as follows:

[0073] in, Indicates the first The engine thrust corresponding to a feasible steady-state support point This represents the thrust neighborhood threshold.

[0074] When there are enough support points near the current thrust reference, the nearest neighbor distance is small, and they are within the mapped support range. Approaching 1; when the number of support points is insufficient, the nearest neighbor distance is too large, or the current thrust reference exceeds the support range, This is reduced. Therefore, in the MPC cost function, it can be reduced... The strength of the fuel economy guide term is adaptively adjusted to avoid the controller relying too heavily on low-reliability parameters. Interpolation result.

[0075] In the MPC cost function, it can be... Multiply by the fuel economy item:

[0076] in, This represents the cost of fuel economy. Indicates the length of the prediction time domain. Indicates the prediction of the first time domain Credibility factor guided by fuel economy. Indicates the weight of fuel economy. Indicates the current sampling time.

[0077] In this embodiment, during online operation, the thrust reference comes from the pilot's throttle lever, the upper-level flight control / mission management system, or the engine thrust scheduler. For desktop simulation or hardware-in-the-loop verification, the APRBS thrust step signal is used as the verification input. APRBS is only used to generate random references covering multiple thrust levels, facilitating the verification of the controller's response, economy, and constraint maintenance capabilities under different thrust variations.

[0078] If the controller does not have a future reference preview, the current thrust target remains unchanged in the prediction time domain: .

[0079] If the upper-level mission system provides future thrust commands or a known APRBS sequence during verification, then a future thrust reference can be used in the prediction time domain:

[0080] Both modes can be obtained in real time through table lookup or interpolation. Therefore, this invention does not require prior knowledge of the complete APRBS sequence; it only requires pre-construction of the fuel economy guide map.

[0081] Step S4 specifically involves: at each sampling time, sampling a locally linear model from the LPV model based on scheduling variables such as the current state, mode switching factor, and nozzle area.

[0082] Alternatively, an incremental model relative to the steady-state bias can be used. This represents the state vector at the next sampling time. Indicates the scheduling variable A defined state matrix, This represents the state vector at the current sampling time. Represents the input matrix, This represents the current control input vector. This represents the steady-state bias or affine term. Indicates the output vector. Indicates the output matrix. Indicates a directly passed matrix. This represents the output bias or affine term, with a prediction time domain length of [value missing]. The control time domain length is The controller controls the increment. As an optimization variable, the future is solved in a rolling manner. Step-by-step control of actions.

[0083] In this embodiment, the model prediction control cost function is specifically as follows:

[0084] in, For thrust tracking, Indicates the thrust tracking weight. This is a deviation item for economical fuel consumption. Indicates the weight of fuel economy. To control incremental penalty items, This represents the control increment weight matrix. Compared to directly using... Unlike other inventions, this invention uses The design expresses the principle of "guided with near-economical fuel near the current thrust requirement." This design prevents the controller from unconditionally pushing the fuel to the lower limit.

[0085] In an embodiment of the present invention, and Do not set a fixed terminal reference or force terminal tracking item. That is, you can set:

[0086] in, This represents the control input reference deviation weight matrix. This represents the reference deviation weight matrix of the control input terminal. This represents a diagonal matrix. Therefore... and It becomes a constrained free collaborative optimization variable, and its adjustment path is jointly determined by thrust tracking, fuel economy, temperature constraints, surge margin constraints, and actuator constraints.

[0087] In this embodiment, the temperature constraint is: .

[0088] The surge margin constraint is: .

[0089] The actuator amplitude constraint is:

[0090] in, This indicates the lower limit of the control input amplitude. This represents the control input vector predicted at time k for the i-th step. This indicates the upper limit of the control input amplitude.

[0091] The actuator rate constraint is:

[0092] in, This indicates the lower limit of the control increment. This represents the i-th control increment predicted at time k. This indicates the upper limit of the control increment.

[0093] The above constraints ensure that the controller does not violate the engine thermal safety boundary, stability margin boundary, and actuator physical boundary when tracking thrust and improving fuel economy.

[0094] In this embodiment, the intermediate region of the VCE's mode switching is used as a resident optimization working region, rather than merely as a transient path that must be traversed quickly between two endpoint modes. Because... and Without being forced to track a preset terminal position, the MPC can guide based on the current thrust target and fuel economy. Constraints and surge margin constraints, selected online. and The median value.

[0095] When the intermediate configuration can meet the thrust requirements at a low cost and maintain safety constraints, the controller can keep the engine running in the intermediate cycle region. When the thrust mission or safety constraints change and the intermediate configuration is no longer preferred, the controller will drive the engine to migrate to a new intermediate configuration or endpoint mode.

[0096] In this embodiment, the fuel economy guidance mapping method based on thrust mission does not directly minimize WFM or WFM². Instead, it constructs WFMeco based on the thrust reference at the LPV steady-state point that satisfies temperature and surge constraints, making the fuel economy term relevant to the current thrust mission. Mechanisms such as AMSV and A8 are not treated as fixed end targets that must be tracked, but as free co-optimization variables, jointly determined by thrust tracking, fuel economy guidance, and safety constraints. The intermediate cycle dwelling optimization mechanism treats the intermediate region of VCE mode switching as a runnable and dwelling continuous cycle adjustment space, rather than just an instantaneous transition segment between endpoint modes. Combined with safety constraints such as T4, the MPC construction method of thrust rapid response and fuel economy indicators ensures that fuel economy optimization does not exceed the engine temperature and stability margin boundaries. The WFMeco interpolation reliability evaluation method under the low-density LPV steady-state grid adjusts or diagnoses the reliability of the fuel economy term based on the number of local support points, nearest neighbor distance, and whether it exceeds the boundary. In actual control, the thrust reference can come from the throttle lever or the mission system; during verification, the APRBS thrust command can be used to cover multiple operating conditions. APRBS does not limit the scope of protection of this application.

[0097] In this embodiment, in addition to finding the minimum WFM based on the LPV steady-state grid, the fuel economy guided mapping can also use engine performance maps, test data, offline scanning results of component-level models, surrogate models, Gaussian process regression, neural network regression, radial basis function interpolation, or piecewise polynomial fitting to obtain WFM_eco.

[0098] In this embodiment, WFM_eco can be input only as thrust FN, or it can be extended to include thrust, flight altitude, Mach number, low-pressure speed, high-pressure speed, mode switching factor, nozzle area or other scheduling variables as input.

[0099] In this embodiment, linear interpolation, nearest neighbor interpolation, piecewise cubic Hermite interpolation, spline interpolation, multidimensional lookup table, local regression, or online optimization search can be used.

[0100] In this embodiment, the confidence level can be constructed from the number of local support points, nearest neighbor distance, interpolation residual, steady-state point coverage density, model error estimation, or online model consistency error; alternatively, instead of explicitly introducing γ, a conservative weight can be switched when the confidence level is low.

[0101] In this embodiment, the predictive control optimization problem can be solved by quadprog, OSQP, qpOASES, active set method, interior point method, or embedded QP solver.

[0102] In this embodiment, the method can be used for verification of real VCE, component-level simulation models, hardware-in-the-loop simulation platforms, digital twin models, or embedded FADEC controllers.

[0103] In this embodiment, in addition to T4 and the three types of surge margin, the upper limit of speed, fuel change rate, pressure ratio, exhaust temperature, actuator position saturation, acceleration limit, combustion stability constraint, etc. can also be added.

[0104] In this embodiment, the thrust reference can be APRBS, step, ramp, mission profile, throttle command, or output from the upper energy management system.

[0105] In this embodiment, intermediate dwell time can be determined naturally by the MPC cost function, or it can be explicitly added with endpoint modal penalties, intermediate region revenue terms, dwell time constraints, or modal region soft constraints.

[0106] The VCE cross-modal control method of this invention, which balances rapid thrust response and fuel economy, can achieve thrust mission tracking, fuel economy guidance, and safety constraint maintenance without forcing geometric variables to follow preset terminal values. This method allows the VCE to reside in the intermediate circulation region between the turbofan and turbojet modes while meeting thrust, temperature, and surge margin constraints, thereby transforming the intermediate mode from a "transition segment that must be traversed as quickly as possible" into an "operating region that can be selected and maintained by the optimizer."

[0107] Example 2: Based on Example 1, this embodiment of the invention provides a control scheme: directly using WFM² as the fuel cost, i.e. This scheme is convenient for comparison in terms of ablation efficiency, but its physical implication—that lower fuel consumption is better—leads to a conflict between fuel economy and rapid thrust response, resulting in poor performance. The main scheme adopts... It does not require fuel to be reduced indefinitely, but rather guides fuel consumption to be close to the current thrust demand for economical fuel.

[0108] By comparing the two cost functions under the same thrust APRBS command, the same LPV model, and the same temperature and surge constraints, the differences in thrust error, cumulative fuel consumption, BETA_MSV / A8 free cooperative trajectory, T4 peak value, minimum surge margin, and solution time can be observed.

[0109] Figure 2 , Figure 3 , Figure 4 and Figure 5 The figure shows a comparison of engine thrust, fuel flow, and speed response under two fuel cost functions. Case 1 corresponds to the direct fuel square penalty scheme, i.e. Scenario 2 corresponds to the economic fuel reference deviation penalty scheme, namely... Under the same thrust conditions, scenarios one and two will result in different fuel regulation patterns and speed response characteristics. Figure 2 Net thrust The time-varying behavior is used to compare the engine's ability to track APRBS thrust commands under the two cost functions. Figure 3 fuel flow The changes over time are used to compare the impact of the direct fuel square penalty and the fuel economy reference deviation penalty on fuel orders, and to provide a fuel economy reference. . Figure 4 For low pressure speed The changes over time are used to observe the impact of the two cost functions on the dynamic response of the engine rotor. Figure 5 High pressure speed How it changes over time.

[0110] Figure 6 and Figure 7 The figure shown is a comparison of the coordinated adjustment of free geometric variables under two fuel cost functions. Figure 6 Indicates mode switching factor How it changes over time. Figure 7 Indicates the tailpipe area The changes over time. Because the method proposed in this invention does not... and A fixed terminal is set to track the target, and the changes in both are determined autonomously by the predictive controller based on thrust tracking, fuel economy, safety constraints, and actuator constraints. Figure 6 and Figure 7 This is used to illustrate that the mode switching factor and the nozzle area are not forced to change according to the preset endpoint trajectory, but rather participate in the control as constrained free collaborative optimization variables.

[0111] Figure 8 , Figure 9 , Figure 10 and Figure 11 This is a comparison chart showing the satisfaction of safety constraints and the real-time performance of optimization solutions under two different fuel cost functions. Figure 8 Indicates turbine temperature Solving time, Figure 9 Indicates fan surge margin Solving time, Figure 10 Indicates the surge margin of a medium-pressure compressor. Solving time, Figure 11 This indicates the QP solution time. The upper or lower limit lines in the figure represent temperature and surge margin constraints, while the 20 ms cutoff line represents the real-time control cycle constraint. Figure 8 , Figure 9 , Figure 10 and Figure 11 Note: Whether the two fuel cost functions can still meet the requirements of temperature constraints, surge margin constraints, and real-time solution when performing thrust tracking and fuel economy adjustment.

[0112] Figure 12 and Figure 13 This is a thrust-fuel economy reference mapping and interpolation support quality diagnostic diagram. Figure 12 exist Plot the feasible steady-state point of LPV, the selected fuel economy support point, and the data obtained by interpolation from the support point on the plane. Curve; if the number of LPV steady-state points near certain support points is insufficient or the nearest neighbor distance is too large, they are marked as weak support points. Figure 13 The number of neighborhood steady-state points and the proportion of nearest neighbor distance to thrust range are given under different thrust support levels. Figure 12 and Figure 13 illustrate It is not arbitrarily set, but is constructed from the LPV steady-state point; at the same time, Figure 12 and Figure 13 It is also used to evaluate the reliability of the fuel economy reference mapping under low-density LPV grids. The 4% nearest neighbor distance threshold is used as the diagnostic benchmark in the figure.

[0113] Figure 14 and Figure 15 A diagram illustrating the online generation process of an economical fuel reference under a given APRBS thrust command. Figure 14 Indicates APRBS thrust step command Changes over time; Figure 15 This indicates the economical fuel reference obtained by online interpolation based on the thrust command. . Figure 14 and Figure 15 Note: This method does not require pre-defining a complete fuel trajectory; instead, it can generate fuel-economical fuel in real time based on thrust references in the current or predicted time domain through thrust-fuel-economical fuel mapping. Therefore, APRBS is only used as a thrust input signal for verification and does not constitute a necessary limitation on the method of this application.

[0114] Figure 16 and Figure 17 This is a diagnostic chart for the fuel economy interpolation quality of each thrust segment in APRBS. Figure 16 Give the number of LPV steady-state support points near the thrust target for each APRBS segment, and set a minimum expected support point number threshold; Figure 17 Give the proportion of the nearest neighbor distance to the thrust range for each APRBS segment, and set an upper limit threshold for the nearest neighbor distance. Figure 16 and Figure 17 Used to determine the thrust target corresponding to each APRBS Does it have sufficient steady-state support points? When a segment has few support points or a large nearest neighbor distance, it indicates that the fuel economy reference reliability of that segment is low, and the fuel economy weight can be reduced or a conservative control strategy can be adopted in the future.

[0115] Example 3: Based on Example 1, this embodiment of the invention provides a VCE cross-modal control system that balances rapid thrust response and fuel economy. This system can be used to implement the VCE cross-modal control method described in the foregoing embodiments, which balances rapid thrust response and fuel economy. The system includes: The first module is used to establish a linear variable parameter steady-state operating condition grid for a variable cycle aero-engine offline, and to perform safety and feasibility screening on the steady-state points in the linear variable parameter steady-state operating condition grid to obtain feasible steady-state points. The second module is used to construct a thrust-economic fuel guide mapping based on a feasible steady-state point. The third module is used to obtain the current thrust reference online, obtain the current economic fuel guidance value according to the thrust-economic fuel guidance mapping, and calculate the confidence factor; The fourth module is used to sample the local linear prediction model from the linear variable parameter steady-state grid based on the current scheduling variables, and to construct the output prediction matrix in the prediction time domain. The fifth module is used to construct the model prediction control cost function based on the output prediction matrix and confidence factor; The sixth module is used to construct hard constraints based on the output prediction matrix, including temperature constraints, surge margin constraints, actuator amplitude constraints, and actuator rate constraints. The seventh module is used to solve the quadratic programming problem of the model predictive control cost function under hard constraints, obtain the control increment sequence, and apply the first control increment to the engine to output control commands for fuel flow, mode switching factor and nozzle area, thus completing VCE cross-modal control.

[0116] According to embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0117] In an exemplary embodiment, an electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method as described in Embodiment 1 above.

[0118] In an exemplary embodiment, the readable storage medium may be a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method described in Embodiment 1 above.

[0119] In an exemplary embodiment, the computer program product includes a computer program that, when executed by a processor, implements the method described in Embodiment 1 above.

[0120] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0121] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0122] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0123] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0124] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0125] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A VCE cross-modal control method that balances rapid thrust response and fuel economy, characterized in that, Includes the following steps: A linear variable parameter steady-state operating condition grid for a variable cycle aero-engine was established offline, and the steady-state points in the linear variable parameter steady-state operating condition grid were screened for safety feasibility to obtain feasible steady-state points. Construct a thrust-economic fuel guide mapping based on a feasible steady-state point; Obtain the current thrust reference online, obtain the current economic fuel guidance value based on the thrust-economic fuel guidance mapping, and calculate the confidence factor; Based on the current scheduling variables, a local linear prediction model is obtained by sampling from the linear variable parameter steady-state operating condition grid, and the output prediction matrix in the prediction time domain is constructed. Construct a model to predict the control cost function based on the output prediction matrix and the confidence factor; Hard constraints are constructed based on the output prediction matrix, including temperature constraints, surge margin constraints, actuator amplitude constraints, and actuator rate constraints. Solve the quadratic programming problem of the model predictive control cost function under hard constraints to obtain the control increment sequence. Apply the first control increment to the engine to output control commands for fuel flow, mode switching factor and nozzle area, thus completing VCE cross-modal control.

2. The VCE cross-modal control method that balances rapid thrust response and fuel economy according to claim 1, characterized in that, The screening criteria for safety feasibility screening of steady-state points in a linear variable parameter steady-state grid include: in, Indicates fuel flow rate. Indicates turbine temperature, Indicates engine thrust. Indicates the fan surge margin. Indicates the surge margin of a medium-pressure compressor. Indicates the surge margin of the high-pressure compressor. This indicates the maximum permissible value for turbine temperature. This represents the minimum allowable value for fan surge margin. This represents the minimum allowable surge margin for a medium-pressure compressor. This indicates the minimum allowable surge margin of a high-pressure compressor.

3. The VCE cross-modal control method that balances rapid thrust response and fuel economy according to claim 1, characterized in that, The method for constructing a thrust-economic fuel-guided mapping based on a feasible steady-state point is as follows: For a given thrust target, determine the set of steady-state points that satisfy the thrust difference threshold among feasible steady-state points. : in, Indicates the first The net engine thrust corresponding to a feasible steady-state point Indicates the thrust neighborhood threshold. Represents the set of feasible steady-state points; Select the steady-state point with the minimum fuel flow rate from the set of steady-state points as the economical fuel guide for a given thrust target: in, Indicates a given thrust target Corresponding fuel economy guidelines Represents the set of steady-state points The selection is based on the principle of minimizing fuel flow. Indicates the first The fuel flow rate corresponding to each feasible steady-state point; By selecting fuel-efficient guidance for multiple thrust targets, a thrust-fuel-efficient guidance mapping table is obtained: in, Indicates the first The thrust support level of each engine Indicates the relationship with the first The fuel economy guidance corresponding to the thrust support level of each engine. This indicates the number of feasible steady-state support points in the thrust-economy fuel guidance mapping table.

4. The VCE cross-modal control method that balances rapid thrust response and fuel economy according to claim 1, characterized in that, The credibility factor is determined by the number of feasible steady-state support points in the thrust neighborhood, the thrust distance between the thrust target and the nearest feasible steady-state point, and whether the thrust target is located within the thrust range covered by the feasible steady-state support points used to construct the WFMeco map. The specific formula is as follows: in, This represents the reliability factor for economical fuel consumption at the current sampling time. Indicates the current thrust reference The number of feasible steady-state support points within the neighborhood; This indicates the minimum expected number of support points. This indicates the thrust distance between the current thrust reference and the nearest feasible steady-state support point; This indicates the preset maximum allowed nearest neighbor distance threshold; This indicates the range coverage flag, which is used when the current thrust reference is within the thrust range covered by the economic fuel guide mapping support point. ,otherwise ; Represents a saturation function; Number of feasible steady-state support points in the current thrust reference neighborhood Thrust distance to nearest neighbor They are represented as follows: in, Indicates the first The engine thrust corresponding to a feasible steady-state support point This represents the thrust neighborhood threshold.

5. The VCE cross-modal control method that balances rapid thrust response and fuel economy according to claim 1, characterized in that, The local linear prediction model is as follows: in, This represents the state vector at the next sampling time. Indicates the scheduling variable A defined state matrix, This represents the state vector at the current sampling time. Represents the input matrix, This represents the current control input vector. Represents the steady-state bias or affine term. Indicates the output vector. Indicates the output matrix. Indicates direct transmission of the matrix. This indicates the output bias or affine term.

6. The VCE cross-modal control method according to claim 1, which balances rapid thrust response and fuel economy, is characterized in that... The output prediction matrix is ​​used to map the future control increment sequence into output prediction values ​​for engine thrust, turbine temperature, fan surge margin, intermediate-pressure compressor surge margin, and high-pressure compressor surge margin in the prediction time domain.

7. The VCE cross-modal control method according to claim 6, which balances rapid thrust response and fuel economy, is characterized in that... Model predictive control cost function Specifically: in, For thrust tracking, Indicates the thrust tracking weight. This is a deviation item for economical fuel consumption. Indicates the weight of fuel economy. To control incremental penalty items, This represents the control increment weight matrix. Indicates the length of the prediction time domain. Indicates in The first time predicted Step engine net thrust, Indicates in Time of the first The corresponding thrust reference for each step Indicates in Time of the first Predicting fuel flow step by step, Indicates in Time of the first The fuel-efficient guide is derived from the thrust target mapping. Indicates in Time of the first Step control increment, superscript Indicates transpose. This indicates the length of the control time domain.

8. The VCE cross-modal control method according to claim 6, which balances rapid thrust response and fuel economy, is characterized in that... Temperature constraints are: in, Indicates in The first time predicted Step turbine temperature, This indicates the maximum permissible value for turbine temperature; The surge margin constraint is: in, Indicates in The first time predicted step fan surge margin, Indicates in The first time predicted Surge margin of the intermediate-pressure compressor. Indicates in The first time predicted High-pressure compressor surge margin, This represents the minimum allowable value for fan surge margin. This represents the minimum allowable surge margin for a medium-pressure compressor. This indicates the minimum allowable surge margin of a high-pressure compressor; The actuator amplitude constraint is: in, This indicates the lower limit of the control input amplitude. This represents the control input vector predicted at time k for the i-th step. This indicates the upper limit of the control input amplitude; The actuator rate constraint is: in, This indicates the lower limit of the control increment. This represents the i-th control increment predicted at time k. This indicates the upper limit of the control increment.

9. The VCE cross-modal control method that balances rapid thrust response and fuel economy according to claim 1, characterized in that, The mode switching factor and nozzle area are not set with fixed terminal tracking targets. Instead, they are used as free collaborative optimization variables, allowing the engine to reside and operate in the intermediate circulation region between the turbofan mode and the turbojet mode.

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