Aero-engine performance model-based full envelope control plan design method and device, computer equipment and medium

Abstract

Embodiments of the present application provide a full envelope control plan design method and device based on an aero-engine performance model, computer equipment and a medium, wherein the method comprises the following steps: generating a discrete simulation point set covering the full flight envelope and full engine operating conditions based on input parameters; setting a minimum disturbance flight operating condition switching rule, sorting the discrete simulation point set according to the minimum disturbance flight operating condition switching rule, and generating an ordered simulation execution path; assigning initial engine state parameters and initial flight envelope environment parameters to the first simulation point in the ordered simulation execution path, simulating the simulation point through the aero-engine performance model, until all simulation points in the ordered simulation execution path are traversed, and storing the model output of all simulation points meeting the convergence condition; and generating a full envelope control plan based on the model output. The speed-height characteristic rapid acquisition technology of the embodiments of the present application improves the calculation efficiency of the full envelope control plan.

Description

Technical Field

[0001] This invention relates to the field of aero-engine control technology, and in particular to a method, apparatus, computer equipment, and medium for designing a full envelope control plan based on an aero-engine performance model. Background Technology

[0002] Advanced aero engines are gradually exhibiting characteristics of wide range, multi-modality, and multi-variable. Furthermore, due to the high difficulty of engine design, the number of times the flight envelope, operating modes, and engine characteristics are updated during the design process increases, which makes the control plan design more difficult and the number of iterations more frequent, making it imperative to improve the efficiency of single control plan design.

[0003] Existing control program design schemes mainly use model simulation data as input, which has the following two problems: (1) The calculation process is complicated due to the large number of unknown state parameters within the wide envelope.

[0004] The performance model using the iterative solution algorithm requires state parameters at different operating points within the full envelope as initial values ​​for iteration during runtime. The wide-range operation characteristic makes the process of obtaining initial values ​​for iteration cumbersome and time-consuming when using traditional control design methods.

[0005] (2) The narrow operating range of multimodal operation makes the performance model prone to divergence.

[0006] Advanced aero engines, in their pursuit of performance limits, have narrower stable operating windows compared to traditional aero engines. They are also more prone to instability under extreme conditions, making it difficult to output model-based stability performance simulation data in this region.

[0007] Meanwhile, when using control plans designed using traditional methods, the state of a multi-modal engine before and after switching modes is very different. Using the same iterative initialization parameters will directly lead to model divergence. Furthermore, due to the wide flight envelope, the state difference between the ground and high altitude is also significant. Using the same iterative initialization parameters will also lead to model divergence, which hinders the speed and altitude characteristic calculation process and makes it difficult to support the design of wide-domain multi-modal control plans. Summary of the Invention

[0008] In view of this, embodiments of the present invention provide a full envelope control plan design method based on an aero-engine performance model to solve the technical problems of low efficiency in acquiring aero-engine performance data and difficulty in designing control plans in the prior art. The method includes: The input parameters are obtained, and based on the input parameters, a set of discrete simulation points covering the entire flight envelope and all engine operating conditions is generated. The input parameters include the boundaries of the flight envelope environmental parameters and the simulation interval of the flight envelope environmental parameters, the boundaries of the engine state parameters and the simulation interval of the engine state parameters, and each simulation point is determined by a specific set of values ​​of the flight envelope environmental parameters and the engine state parameters. Set minimum disturbance flight condition switching rules, sort the discrete simulation point set according to the minimum disturbance flight condition switching rules, and generate an ordered simulation execution path; Initialize the aero-engine performance model, assign the initial engine state parameters and initial flight envelope environment parameters to the first simulation point in the ordered simulation execution path, perform simulation calculations on the simulation point through the aero-engine performance model, until all simulation points in the ordered simulation execution path are traversed, and store the model output of all simulation points that meet the convergence conditions. A full envelope control plan is generated based on the output of the model.

[0009] This invention also provides a full-envelope control plan design device based on an aero-engine performance model to solve the technical problems of low efficiency in acquiring aero-engine performance data and difficulty in designing control plans in the prior art. The device includes: The input parameter determination module is used to acquire input parameters and, based on the input parameters, generate a set of discrete simulation points covering the entire flight envelope and all engine operating conditions. The input parameters include the boundaries of the flight envelope environmental parameters and the simulation interval of the flight envelope environmental parameters, the boundaries of the engine state parameters and the simulation interval of the engine state parameters, and each simulation point is uniquely determined by a specific set of values ​​of the flight envelope environmental parameters and the engine state parameters. The simulation execution path generation module is used to set the minimum disturbance flight condition switching rules, sort the discrete simulation point set according to the minimum disturbance flight condition switching rules, and generate an ordered simulation execution path. The simulation module is used to initialize the aero-engine performance model, assign initial state parameters and initial inputs to the first simulation point in the ordered simulation execution path, perform simulation calculations on the simulation point through the aero-engine performance model, until all simulation points in the ordered simulation execution path are traversed, and store the model output of all simulation points that meet the convergence conditions. The control plan generation module is used to generate a full envelope control plan based on the model output.

[0010] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned full envelope control plan design methods based on the aero-engine performance model, thereby solving the technical problems of low efficiency in acquiring aero-engine performance data and difficulty in designing control plans in the prior art.

[0011] This invention also provides a computer-readable storage medium storing a computer program that executes any of the above-described full envelope control plan design methods based on an aero-engine performance model, in order to solve the technical problems of low efficiency in acquiring aero-engine performance data and difficulty in designing control plans in the prior art.

[0012] Compared with the prior art, the beneficial effects that at least one technical solution adopted in the embodiments of this specification can achieve include at least: The full-envelope control scheme of this invention significantly improves the computational efficiency of speed-height characteristics. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart of a full envelope control plan design method based on an aero-engine performance model provided by an embodiment of the present invention; Figure 2 This is a logical architecture diagram of an embodiment of the present invention for implementing the above-described full envelope control plan design method based on an aero-engine performance model; Figure 3 This is a simplified logical architecture diagram; Figure 4 It is a design loop tuner for the PI architecture provided in the embodiments of the present invention; Figure 5 This is a flowchart of a full envelope control plan design method based on an aero-engine performance model provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of high Mach number simulation path planning provided in one embodiment of the present invention; Figure 7 This is a schematic diagram of rotational speed simulation path planning provided in one embodiment of the present invention; Figure 8 This is a flowchart of the simulation output process provided in one embodiment of the present invention; Figure 9 This is a schematic diagram illustrating the first relationship between fuel flow rate and physical rotational speed according to an embodiment of the present invention; Figure 10 This is a schematic diagram illustrating the second relationship between fuel flow rate and physical rotational speed, provided in one embodiment of the present invention; Figure 11 This is a structural block diagram of a computer device provided in an embodiment of the present invention; Figure 12 This is a structural block diagram of a full envelope control planning and design device based on an aero-engine performance model provided in an embodiment of the present invention. Detailed Implementation

[0015] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0016] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] In this embodiment of the invention, a method for designing a full envelope control plan based on an aero-engine performance model is provided, such as... Figure 1 As shown, the method includes: Step S101: Obtain input parameters, and based on the input parameters, generate a set of discrete simulation points covering the entire flight envelope and all engine operating conditions. The input parameters include the boundaries of the flight envelope environmental parameters and the simulation interval of the flight envelope environmental parameters, the boundaries of the engine state parameters and the simulation interval of the engine state parameters, and each simulation point is determined by a specific set of values ​​of the flight envelope environmental parameters and the engine state parameters. Step S102: Set the minimum disturbance flight condition switching rules, and sort the discrete simulation point set according to the minimum disturbance flight condition switching rules to generate an ordered simulation execution path; Step S103: Initialize the aero-engine performance model, assign the initial engine state parameters and initial flight envelope environment parameters to the first simulation point in the ordered simulation execution path, perform simulation calculations on the simulation point through the aero-engine performance model, until all simulation points in the ordered simulation execution path are traversed, and store the model output of all simulation points that meet the convergence conditions. Step S104: Generate a full envelope control plan based on the model output.

[0018] In specific implementation, the following steps are used to set the minimum disturbance flight condition switching rules, and based on the minimum disturbance flight condition switching rules, the discrete simulation point set is sorted to generate an ordered simulation execution path: After fixing the flight envelope environmental parameters and adjusting the engine state parameters, fix the engine state parameters again, and then sequentially adjust the flight envelope environmental parameters as the minimum disturbance flight condition switching rule; calculate the distance between the next simulation point and the current simulation point in the flight envelope coordinate system. ,in, m The total number of the flight envelope environmental parameters. i These are the simulation points for the flight envelope environmental parameters. i’ for i The next simulation point, Env This is the parameter vector of the flight envelope environmental parameters. n The total number of the engine state parameters. j These are the simulation points for the engine state parameters. j’ for j The next simulation point, Eng The parameter vector of the engine state parameters; the distance L The shortest route is taken as the ordered simulation execution path.

[0019] In specific implementation, the simulation calculations for simulation points are performed using the aero-engine performance model through the following steps, until all simulation points in the ordered simulation execution path are traversed, and the model output of all simulation points that meet the convergence conditions is stored: Following the ordered simulation execution path, traverse all simulation points in the ordered simulation execution path: Set the current engine state parameter X( k ) and the current flight envelope environmental parameters U( k The input is fed into the aero-engine performance model to generate the model output Y( k ) and model residual e( k ),in, k The simulation point is used; the model residual e( k The model residual e is compared with the preset convergence criterion ε and the result is used to determine the model residual e(k The convergence criterion ε is used as the convergence condition; if the convergence condition is met, the state update is initiated, and the next engine state parameter X is updated. k +1) Set to the new engine state parameter X obtained after convergence of the current simulation point. new ( k If the convergence condition is not met, enter state holding mode and set the next engine state parameter X( k +1) is set to the engine state parameter X input before the current simulation point calculation. k ); Store the model output Y( that satisfies the convergence condition. k ).

[0020] In practice, the execution status rollback is achieved through the following steps: If the number of times the state is maintained exceeds a preset threshold or the simulated value of the engine state parameter exceeds the physically valid range, a state rollback is executed: the next engine state parameter X( k +1) Revert to the first simulation point in the ordered simulation execution path that satisfies the convergence condition under the current flight envelope environmental parameters. l Corresponding engine state parameter X new ( l ).

[0021] In practice, the use of the loop tuner is achieved through the following steps: When performing simulation calculations on simulation points using the aero-engine performance model, a loop tuner is set between the input and output of the aero-engine performance model; the loop tuner is based on a proportional-integral (PI) control architecture and is used to adjust the closed-loop zeros and poles of the system; the loop tuner includes a designed loop tuner and a non-designed loop tuner.

[0022] In practice, the input parameters are defined through the following steps: The flight envelope environmental parameters include environmental input altitude H and Mach number Ma; the engine status parameters include high-pressure rotor speed NH, low-pressure rotor speed NL, exhaust temperature T5, engine pressure ratio EPR, compressor pressure ratio πc, turbine pressure ratio πT, and bypass ratio BPR; the input parameters also include engine controllable input parameters, which include fuel flow rate Wf and exhaust nozzle area A8.

[0023] In practice, the following steps are used to generate a full envelope control plan based on the model output: Extract the parameter dataset related to the target control plan from the model output. The parameter dataset includes control variables, flight envelope environmental parameters, and engine state parameters. Based on the parameter dataset, a functional relationship between the control quantity and the flight envelope environmental parameters and engine state parameters is established using a modeling method. ,in, u The output control quantity, Env This is the parameter vector of the flight envelope environmental parameters. Eng The parameters are those of the engine state parameters; if the control quantity u is linearly related to only one of the engine state parameters, the functional relationship is simplified to... or ,in, k The slope of a linear function. b The intercept of the linear function is given by g(), and the correction function is given by g(). The simplified functional relationship is used as the control plan.

[0024] Aero-engines are nonlinear systems with strong coupling across multiple disciplines. Their dynamic characteristics can be represented by a system of nonlinear equations, which can be solved using iterative algorithms. Aero-engine performance models can use inputs U (including uncontrollable environmental inputs such as altitude H and Mach number Ma, and controllable adjustment inputs such as fuel flow rate Wf and exhaust nozzle area A8), states X (parameters representing the engine's current operating state, including but not limited to high-pressure rotor speed NH, low-pressure rotor speed NL, exhaust temperature T5, engine pressure ratio EPR, compressor pressure ratio πc, turbine pressure ratio πT, and bypass ratio BPR), and outputs Y (including cross-sectional parameters such as temperature T, pressure P, flow rate W, and fuel-air ratio f at various engine sections, and performance parameters such as engine thrust F and fuel consumption rate sfc). Taking a single-shaft turbofan engine as an example, the typically selectable inputs are altitude H, Mach number Ma, and fuel flow rate Wf; the states are rotor physical speed N, compressor pressure ratio πc, and turbine pressure ratio πT; and the outputs are cross-sectional parameters and performance parameters. For aero-engine performance models using iterative solution algorithms, given an initial input U0, a preliminary guess value X0_hat that deviates closely from the true X0 is required; otherwise, the model will struggle to converge. Obtaining X0_hat at different altitudes H, Mach numbers Ma, and fuel flow rates Wf across the entire flight envelope has become a complex and tedious task, consuming significant manpower and time. This is especially true as advanced aero-engine structures become increasingly complex, leading to a substantial increase in input and state variables. Therefore, an efficient method for obtaining the preliminary guess value X0_hat across the entire flight envelope and all operating conditions is urgently needed. Only by obtaining a sufficient number of preliminary guess values ​​X0_hat under various environments and operating conditions can the corresponding output parameters be calculated from the model for control plan design. "Sufficiently sufficient" means covering the entire flight envelope and extreme cases such as the boundaries of operating conditions, and taking a series of points within the envelope. The denser the point selection, the greater the information content and the more accurate the final control plan, but the greater the computational burden.

[0025] The embodiments of this invention can support the need for large-scale point-based calculations and design control plans under different operating conditions within the entire coverage area, significantly improving computational efficiency. For example... Figure 6 As shown, the Mach number interval is set to 0.2, the altitude interval to 2km, and the speed interval to 2% (setting the speed interval to 2% is a control plan design method that contains sufficient and effective information). However, this embodiment of the invention supports more granular methods such as setting the Mach number interval to 0.1, the altitude interval to 1km, and the speed interval to 1%.

[0026] For a single-shaft turbojet engine, the height H, Mach number Ma, and fuel flow rate Wf are fixed, while the state X is unique. Therefore, a physical speed percentage (e.g., Figure 4 (As shown) replaces fuel flow rate Wf. Because the fuel flow rate is very small, it is not as intuitive to take the point as using the physical speed percentage. Of course, exhaust temperature T5 can also be used to replace fuel flow rate Wf, any state quantity is acceptable, or fuel flow rate can be used directly. This embodiment of the invention uses physical speed percentage. The goal is to achieve equally spaced points for the three inputs, thereby obtaining the state and output of the corresponding points. Among them, height H and Mach number Ma represent the environment, and fuel flow rate Wf represents the engine's own operating condition.

[0027] In the full envelope control planning design method based on the aero-engine performance model of this invention, the designed solution logic framework is as follows: Figure 2 As shown, the system includes design inputs (the constraints of this design, including the upper and lower boundaries of parameters such as altitude H, Mach number Ma, and fuel flow rate Wf), a performance model (an aero-engine performance model using an iterative solution algorithm), a design loop tuner (enhancing system closed-loop stability), a non-design loop tuner (enhancing system closed-loop stability), and a state / storage selector (recording the initial X value of this simulation). old =X and X after the simulation ends new The system selects the model's input (X), output memory, and control plan design module based on the model residuals. Here, X represents the model state, U represents the model input, Y represents the model output, and e represents the model residual. When e > ε, the model has not converged, and the parameters are invalid (ε is a specified convergence value, typically set to 10⁻⁶).

[0028] By solving the logical framework, it can be guaranteed that X old (e>ε) or X new When (e<ε) is used as the X input for the next time step, the deviation from the actual state at the next time step is limited, thus ensuring the continuity of the calculation throughout the design process and improving design efficiency. Similarly, in the two loop tuners, the closed-loop zeros and poles of the system are adjusted by using architectures such as PI to improve the closed-loop stability of the system and ensure the feasibility of the design process.

[0029] 1. Logical architecture of the full envelope control plan design method based on aero-engine performance model.

[0030] The full-envelope control plan design method based on an aero-engine performance model in this invention can significantly improve computational efficiency and support the need for large-scale point-based calculation and control plan design under different operating conditions within the full envelope. For example... Figure 6 As shown, setting the Mach number interval to 0.2, the height interval to 2km, and the speed interval to 2% is a control plan design method that incorporates sufficient and effective information.

[0031] For a single-shaft turbojet engine, the height H, Mach number Ma, and fuel flow rate Wf are fixed, and the state X is unique. Therefore, a physical speed percentage can be used instead of fuel flow rate Wf. Since the fuel flow rate is very small, using a physical speed percentage is more intuitive. Alternatively, exhaust temperature T5 can be used instead of fuel flow rate Wf; any state variable is acceptable, or fuel flow rate can be used directly. This embodiment uses a physical speed percentage. The goal is to achieve equally spaced points for the three inputs, thereby obtaining the state and output at the corresponding points. Here, height H and Mach number Ma represent the environment, and fuel flow rate Wf represents the engine's own operating conditions.

[0032] The embodiments of the present invention support more granular intervals, such as setting the Ma number interval to 0.1, the height interval to 1km, and the rotational speed interval to 1%.

[0033] like Figure 2 As shown, the solution logic framework of the full envelope control planning design method based on the aero-engine performance model in this embodiment of the invention includes design inputs (the design constraint range, including the upper and lower boundaries of parameters such as altitude H, Mach number Ma, and fuel flow rate Wf), a performance model (an aero-engine performance model using an iterative solution algorithm), a design loop tuner (enhancing system closed-loop stability), a non-design loop tuner (enhancing system closed-loop stability), and a state / storage selector (recording the initial X value of this simulation). old =X and X after the simulation ends new The system selects the model's input (X), output memory, and control plan design module based on the model residuals. Here, X represents the model state, U represents the model input, Y represents the model output, and e represents the model residual. When e > ε (ε is a specified convergence value, typically set to 10⁻⁶), it indicates that the model has not converged and the parameters are invalid.

[0034] Specifically, the design loop tuner refers to the tuner that adjusts the dynamic response of the system and realizes engine state servo tracking in the loop formed by the target input u and the feedback parameter y during the control plan design process. The non-design loop tuner refers to the tuner that outputs other necessary inputs to maintain the operation of the engine model, and is used to maintain a reasonable expected engine state and ensure the stability of the closed loop system during the design process.

[0035] This framework guarantees that X old (e>ε) or X new When (e<ε) is used as the X input for the next time step, the deviation from the actual state at the next time step is limited, thus ensuring the continuity of the calculation throughout the design process and improving design efficiency. Similarly, in the two loop tuners, the closed-loop zeros and poles of the system are adjusted by using architectures such as PI to improve the closed-loop stability of the system and ensure the feasibility of the design process.

[0036] 2. Technique for quickly obtaining initialization parameters for the full envelope model.

[0037] The technology for rapidly obtaining initialization parameters of the full envelope model is the core of the full envelope control plan design method based on the performance model of the aero-engine, and mainly relies on the minimum disturbance path planning and state parameter selection mechanism.

[0038] (1) Minimum disturbance path planning.

[0039] Only one of multiple input parameters is adjusted at a time, and the path direction is selected according to the principle of minimum adjustment. Typically, the environmental parameters are fixed first, the engine state is adjusted, then the engine state is fixed, and the environmental parameters are adjusted sequentially. Taking the three variables of height H, Mach number Ma, and physical speed N as an example, when the physical speed N of two adjacent simulation points changes, the height H and Mach number Ma must remain unchanged (i.e., under fixed height H and Mach number Ma, the physical speed N changes sequentially until it covers all operating conditions from slow to heavy). When the height H of two adjacent simulation points changes, the physical speed N and Mach number Ma must remain unchanged (after changing to a new height H', the physical speed N is changed sequentially again until it covers all operating conditions from slow to heavy). When the Mach number Ma of two adjacent simulation points changes, the physical speed N and height H must remain unchanged (after changing to a new Mach number Ma', the physical speed N is changed sequentially again until it covers all operating conditions from slow to heavy). Meanwhile, the flight condition switching rule designed in this invention is as follows: when switching flight conditions, the distance between the next simulation point (which has not been simulated before) and the current simulation point in the flight envelope coordinate system is the shortest. This can be expressed by the following formula:

[0040] This formula ensures that when flight conditions change, Ma is changed first, followed by H. This is because the range of H is typically 1 to 2, while the range of Ma is typically 0.1 to 0.2.

[0041] When the physical rotational speed N is normalized, i.e., N ranges from 0 to 1, its variation range is 1% to 2%, and the above formula can be further extended to: .

[0042] For cases with more parameters, minimum disturbance path planning is divided into two parts: environmental changes (flight envelope environmental parameters) and engine operating conditions (engine state parameters). Environmental changes, besides H and Ma, can also consider standard sea level temperature (ISA) and air humidity, etc. Engine operating conditions, besides being represented by N, can also be represented by engine pressure ratio (EPR), turbine pressure ratio (Πt), exhaust temperature (T5), etc. For multi-shaft aero-engines, multiple parameters are needed to characterize engine operating conditions, such as engine low-pressure physical speed (N1) and engine high-pressure physical speed (N2), etc., which are not general. Therefore, the generalized way to write the above formula is:

[0043] in, m The number of parameters used to represent environmental changes. n This indicates the number of parameters used to represent engine variations. Env Represents a vector of parameters indicating environmental changes. Eng This represents the vector of engine variation parameters. Minimum disturbance path planning is: .

[0044] (2) State parameter selection mechanism.

[0045] The state selection mechanism of this invention is divided into three cases: state update, state maintenance, and state rollback.

[0046] In the initial stage of the simulation, the state parameter X0 of the ground slow vehicle or the ground large vehicle is given, denoted as X old The performance model obtains the new state parameters X at the current point at the end of each simulation. new Because a minimum disturbance path planning simulation sequence is used, when the density of simulation points is appropriate (i.e., the same number of simulation points as in traditional design schemes), the convergence of the performance model when calculating the next state using the current state parameters can be guaranteed, i.e., X=X. new This allows for continuous updating of state parameters and continuous simulation, which is defined as state updating in this invention. However, there are two special cases: First, if the model diverges due to unreasonable input or simulation points exceeding the engine's effective operating range (i.e., e > ε), the state parameters should not be updated. Instead, the parameters X that ensured the convergence of the engine performance model at the previous moment should be updated. old Continuing with the simulation of the next point, this situation is defined in this invention as state preservation, i.e., X=X old .

[0047] Secondly, the simulation boundary selection is unreasonable, such as when the lower boundary N given in the design input is much smaller than the actual reasonable idle speed N. idle When, below N idle The part is invalid information. At this time, the state parameters are adjusted to the state before several simulation points in time. In this invention, this situation is defined as state rollback, that is, for the problem of a certain parameter of the aero-engine itself exceeding the limit or the environmental change parameter exceeding the limit.

[0048] Taking the three variables H, Mach number Ma, and physical rotational speed N as an example, when the height H and Mach number Ma are fixed, the physical rotational speed N changes from the trolley N... max Simulation down to below slow N idle At this time, the state parameters can be rolled back to the current height H and Mach number Ma, where N is the current value. max Then, the next simulation points H', Ma, and N are carried out. max .

[0049] (3) Methods to enhance the closed-loop stability of the system.

[0050] To address the issue of narrow operating windows in advanced, complex engine structures, a loop tuning module is introduced to enhance system stability while ensuring rapid system adjustment and servo tracking capabilities for feedback signals. For simple aero-engines where engine operating states are directly distinguished by fuel flow rate (Wf), this module is not essential. Taking multivariate control of fuel flow rate (Wf) and nozzle throat area (A8) as an example, and designing a control plan with Wf as the objective... Figure 2 It can be simplified to Figure 3 .

[0051] When engine operating conditions need to be characterized by parameters such as physical speed N or exhaust temperature T5, a loop tuner is required. The quality of the tuner's parameter design will affect the closed-loop stability of the system; good parameter design will improve stability without increasing settling time. Taking a PI architecture-based loop tuner as an example, its structure is as follows: Figure 4 As shown, at this point, parameters for P and I need to be given to achieve the adjustment of the system's closed-loop response performance.

[0052] (4) Control design.

[0053] The goal of control design is to obtain the control output u of the aero-engine under all operating conditions within its full envelope. The generalized mathematical expression is as follows: .

[0054] But directly Env and Eng Considering all parameters would make the relationship complex and difficult to fit, and there is also a risk of overfitting. Therefore, the key step in control design is to analyze and fit the simplest relationship between the control quantity and environmental and engine parameters, remove low-correlation variables, and ensure that the fitted formula has a linear relationship (this only refers to the step of finding the pattern and fitting; the final control plan does not need to be linear). Commonly used methods include, but are not limited to, using formulas to calculate the reduced parameters, adding, subtracting, multiplying, dividing, taking square roots, and squaring highly correlated parameters. (The example below shows how a linear relationship was found between the reduced fuel flow rate and the reduced physical speed ncor, thus designing the relationship between the control quantity wf and the physical speed n, the inlet total temperature Tt and the inlet total pressure Pt, i.e., the control law of fuel flow rate).

[0055] When the control variable u is linearly related only to a certain parameter characterizing engine operating conditions, and the influence of environmental parameters has a clear correction formula g(Env), then the general formula can be transformed into:

[0056] or

[0057] A single control variable is linearly related to a single engine operating condition, and environmental factors are considered by adjusting this relationship. Quadratic relationships can also be used, but their usage is very low, and relationships beyond quadratic are generally not used.

[0058] (5) The conversion relationship between environmental parameters and engine sensor measurements.

[0059] The input parameters of this invention include flight envelope altitude H and Mach number Ma. However, for aero engines, H and Ma are not directly measured. More commonly, inlet total temperature T2t and inlet total pressure P2t are used. The relationship between altitude H and Mach number Ma and inlet total temperature T2t and inlet total pressure P2t is shown below: when hour, ; ; when hour, ; ;

[0060] in, PH is the atmospheric pressure at an altitude of 11km, TH is the ambient pressure, and PH is the ambient temperature.

[0061] Therefore, the total inlet temperature T1t and total pressure P1t of the intake manifold are respectively:

[0062]

[0063] Therefore, the total engine inlet temperature T2t and total pressure P2t are respectively:

[0064]

[0065] in, This is the intake manifold total pressure recovery coefficient.

[0066] like Figure 5 As shown, in one embodiment of the present invention, the design process of the main fuel control plan for a certain type of multi-mode aero-engine turbofan mode in its part of the subsonic flight envelope (flight altitude 0~4km, flight Mach number 0~0.8Ma) is used as an example to illustrate the present invention.

[0067] 1. Flight envelope input and simulation route planning.

[0068] Based on the flight envelope, simulation points are extracted. The simulation interval for altitude H is selected as 2, and the simulation interval for maximum altitude (Ma) is 0.2. The flight condition switching rules according to this embodiment are shown in Table 1. The planned simulation path is as follows: Figure 6 As shown.

[0069] Table 1 Simulation Points of Flight Envelope

[0070] 2. Speed ​​range input and simulation path planning.

[0071] The selected speed range is 90%~100% of the main vehicle speed. Speed ​​simulation points are extracted at 2% intervals, as shown in Table 2. The path planning is as follows: Figure 7 As shown. That is, it is necessary to complete [the task] under each environmental condition. Figure 7 Calculation of all engine operating points shown.

[0072] Table 2 Simulation points under different working conditions

[0073] 3. Simulation circuit and parameter settings.

[0074] This design of the turbofan mode main fuel control scheme only studies the relationship between the main fuel flow rate Wf and the engine speed N, altitude H, and Mach number Ma. Therefore, the controlled variable method is used to ensure the consistency of other variables in this design. The nozzle throat area A8 is kept constant. At the same time, considering the surge characteristics of the fan and CDFS in the turbofan mode of the variable mode engine, the surge margin of the engine fan and CDFS components is adjusted by using the fan guide vane angle and CDFS guide vane angle.

[0075] Meanwhile, the simulation parameters were set as follows: to ensure accurate extraction of steady-state data, the single simulation time was set to 500s, the PI parameters of the main fuel control loop were all set to 0.1, and the convergence criterion ε = 10⁻⁶. Based on the flight envelope and speed range, imax = 90.

[0076] The simulation output process is as follows Figure 8 As shown in Table 3, given the fuel flow rate U(1) at the ground point and the initial state value X(0) of the engine model, the composition of the vector X(0) is as follows.

[0077] Table 3. Composition of vector X(0) in this example

[0078] After each model run, if the result converges (i.e., the model output residual e < ε), then the state X is updated to the current model state. If the result does not converge (i.e., the model output residual e > ε), then the current state X is maintained. By following the planned path, the performance parameters of all operating points can be calculated step by step with small state changes, maintaining computational efficiency, model convergence, and system stability.

[0079] 4. Control design.

[0080] Step 3 obtains the output data Y, which includes engine cross-sectional temperature and pressure parameters, speed parameters, performance parameters, etc. Identify the speed, temperature, pressure, and fuel flow parameters relevant to the control plan design. The relationship between fuel flow and physical speed is as follows: Figure 9 As shown.

[0081] By converting fuel flow rate and engine speed using the following formulas, the relationship between the converted fuel flow rate Wfcor and the converted engine speed Ncor can be obtained as follows: Figure 10 As shown.

[0082]

[0083]

[0084] The relationship between the converted fuel flow rate Wfcor and the converted engine speed Ncor can be expressed as:

[0085] Substituting into the conversion formula above, we can obtain the main fuel control plan under the turbofan mode in a given flight envelope as follows:

[0086] In this embodiment, a computer device is provided, such as... Figure 11 As shown, it includes a memory 1101, a processor 1102, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned full envelope control plan design methods based on the aero-engine performance model.

[0087] Specifically, the computer device can be a computer terminal, a server, or a similar computing device.

[0088] In this embodiment, a computer-readable storage medium is provided, which stores a computer program that executes any of the above-described full envelope control plan design methods based on an aero-engine performance model.

[0089] Specifically, computer-readable storage media include both permanent and non-permanent, removable and non-removable media, which can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer-readable storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable storage media do not include transient media, such as modulated data signals and carrier waves.

[0090] Based on the same inventive concept, this invention also provides a full-envelope control planning and design apparatus based on an aero-engine performance model, as described in the following embodiments. Since the principle of the full-envelope control planning and design apparatus based on an aero-engine performance model is similar to that of the full-envelope control planning and design method based on an aero-engine performance model, the implementation of the full-envelope control planning and design apparatus based on an aero-engine performance model can refer to the implementation of the full-envelope control planning and design method based on an aero-engine performance model; repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0091] Figure 12 This is a structural block diagram of a full envelope control planning and design device based on an aero-engine performance model according to an embodiment of the present invention, such as... Figure 12 As shown, it includes: input parameter determination module 1201, simulation execution path generation module 1202, simulation module 1203 and control plan generation module 1204. The structure is described below.

[0092] The input parameter determination module 1201 is used to acquire input parameters and, based on the input parameters, generate a set of discrete simulation points covering the entire flight envelope and all engine operating conditions. The input parameters include the boundaries of the flight envelope environmental parameters and the simulation interval of the flight envelope environmental parameters, the boundaries of the engine state parameters and the simulation interval of the engine state parameters, and each simulation point is uniquely determined by a specific set of values ​​of the flight envelope environmental parameters and the engine state parameters. The simulation execution path generation module 1202 is used to set the minimum disturbance flight condition switching rules, sort the discrete simulation point set according to the minimum disturbance flight condition switching rules, and generate an ordered simulation execution path. The simulation module 1203 is used to initialize the aero-engine performance model, assign the initial state parameters and initial input to the first simulation point in the ordered simulation execution path, perform simulation calculations on the simulation point through the aero-engine performance model, until all simulation points in the ordered simulation execution path are traversed, and store the model output of all simulation points that meet the convergence conditions. The control plan generation module 1204 is used to generate a full envelope control plan based on the model output.

[0093] In one embodiment, the input parameter determination module includes: An environmental parameter determination unit is used to determine the flight envelope environmental parameters, including environmental input altitude H and Mach number Ma. The state parameter determination unit is used to determine the engine state parameters, including high-pressure rotor speed NH, low-pressure rotor speed NL, exhaust temperature T5, engine pressure ratio EPR, compressor pressure ratio πc, turbine pressure ratio πT, and bypass ratio BPR. An engine controllable input parameter determination unit is used for determining the input parameters, which further include engine controllable input parameters, including fuel flow rate Wf and tailpipe area A8.

[0094] In one embodiment, the simulation execution path generation module includes: The switching rule determination unit is used to fix the flight envelope environmental parameters, adjust the engine state parameters, fix the engine state parameters, and then adjust the flight envelope environmental parameters in sequence as the minimum disturbance flight condition switching rule. The distance calculation unit is used to calculate the distance between the next simulation point and the current simulation point in the flight envelope coordinate system. ,in, m The total number of the flight envelope environmental parameters. i These are the simulation points for the flight envelope environmental parameters. i’ for i The next simulation point, Env This is the parameter vector of the flight envelope environmental parameters. n The total number of the engine state parameters. j These are the simulation points for the engine state parameters. j’ for j The next simulation point, Eng This is the parameter vector of the engine state parameters; Generate execution path units to calculate distances L The shortest route is taken as the ordered simulation execution path.

[0095] In one embodiment, the simulation module includes: The loop unit is used to traverse all simulation points in the ordered simulation execution path according to the ordered simulation execution path: The model output unit is used to output the current engine state parameters X( k ) and the current flight envelope environmental parameters U( k The input is fed into the aero-engine performance model to generate the model output Y( k ) and model residual e( k ),in, k For simulation points; Convergence condition setting unit, used to compare the model residual e( k The model residual e is compared with the preset convergence criterion ε and the result is used to determine the model residual e( kThe convergence criterion ε is used as the convergence condition. The convergence condition unit is used to enter the state update if the convergence condition is met, and update the next engine state parameter X( k +1) Set to the new engine state parameter X obtained after convergence of the current simulation point. new ( k ); The unit that does not meet the convergence condition is used to enter state holding if the convergence condition is not met, and to set the next engine state parameter X( k +1) is set to the engine state parameter X input before the current simulation point calculation. k ); The model output unit is used to store the model output Y( that satisfies the convergence condition). k ).

[0096] In one embodiment, the simulation module further includes: The state rollback unit is used to execute state rollback when the number of times the state is maintained exceeds a preset threshold or the simulated value of the engine state parameters exceeds the physically valid range. The parameter processing unit is used to process the next engine state parameter X( k +1) Revert to the first simulation point in the ordered simulation execution path that satisfies the convergence condition under the current flight envelope environmental parameters. l Corresponding engine state parameter X new ( l ).

[0097] In one embodiment, the simulation module further includes: A tuner unit is provided to set a loop tuner between the input and output of the aero-engine performance model when performing simulation calculations on simulation points using the aero-engine performance model. The system unit is adjusted for the loop tuner based on a proportional-integral PI control architecture and for adjusting the closed-loop zeros and poles of the system. A tuner classification unit is used for the circuit tuners, including designed circuit tuners and non-designed circuit tuners.

[0098] In one embodiment, the simulation execution path generation module includes: The parameter extraction unit is used to extract a parameter dataset related to the target control plan from the model output. The parameter dataset includes control variables, flight envelope environmental parameters, and engine state parameters. The function modeling unit is used to establish, based on the parameter dataset, the functional relationship between the control quantity and the flight envelope environmental parameters and the engine state parameters using a modeling method. ,in, u The output control quantity, Env This is the parameter vector of the flight envelope environmental parameters. Eng These are the parameters of the engine state parameters; The function simplification unit is used to simplify the functional relationship as follows if the control quantity u is linearly related to only one of the engine state parameters: or ,in, k The slope of a linear function. b g is the intercept of the linear function, and g() is the correction function; The simplified functional relationship is used as the control plan.

[0099] The embodiments of the present invention achieve the following technical effects: Compared with traditional control planning design methods, the embodiments of the present invention can automatically and continuously acquire state parameters during the simulation process. When an abnormal state occurs, the state can be backtracked in time to ensure the smooth progress of the simulation calculation, significantly improving the calculation efficiency of speed and altitude characteristics, and effectively supporting the iterative design of flight envelope, operating mode and engine characteristics in the engine design process.

[0100] The above description is merely a specific embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any substitution of equivalent components or equivalent changes and modifications made within the scope of protection of this patent should still fall within the scope of this patent. Furthermore, the technical features, technical features and technical solutions, and technical solutions in this invention can be freely combined and used.

Claims

1. A method for designing a full envelope control plan based on an aero-engine performance model, characterized in that, Includes the following steps: The input parameters are obtained, and based on the input parameters, a set of discrete simulation points covering the entire flight envelope and all engine operating conditions is generated. The input parameters include the boundaries of the flight envelope environmental parameters and the simulation interval of the flight envelope environmental parameters, the boundaries of the engine state parameters and the simulation interval of the engine state parameters, and each simulation point is determined by a specific set of values ​​of the flight envelope environmental parameters and the engine state parameters. Set minimum disturbance flight condition switching rules, sort the discrete simulation point set according to the minimum disturbance flight condition switching rules, and generate an ordered simulation execution path; Initialize the aero-engine performance model, assign the initial engine state parameters and initial flight envelope environment parameters to the first simulation point in the ordered simulation execution path, perform simulation calculations on the simulation point through the aero-engine performance model, until all simulation points in the ordered simulation execution path are traversed, and store the model output of all simulation points that meet the convergence conditions. A full envelope control plan is generated based on the output of the model.

2. The full envelope control planning design method based on an aero-engine performance model according to claim 1, characterized in that, A minimum disturbance flight condition switching rule is set, and the discrete simulation point set is sorted according to the minimum disturbance flight condition switching rule to generate an ordered simulation execution path, including: After fixing the flight envelope environmental parameters and adjusting the engine state parameters, fix the engine state parameters and then adjust the flight envelope environmental parameters in sequence as the minimum disturbance flight condition switching rule. Calculate the distance between the next simulation point and the current simulation point in the flight envelope coordinate system. ,in, m The total number of the flight envelope environmental parameters. i These are the simulation points for the flight envelope environmental parameters. i’ for i The next simulation point, Env This is the parameter vector of the flight envelope environmental parameters. n This represents the total number of engine state parameters. j These are the simulation points for the engine state parameters. j’ for j The next simulation point, Eng This is the parameter vector of the engine state parameters; Distance L The shortest route is taken as the ordered simulation execution path.

3. The full envelope control planning design method based on an aero-engine performance model according to claim 1, characterized in that, The simulation calculations are performed on the simulation points using the aero-engine performance model until all simulation points in the ordered simulation execution path are traversed, and the model output of all simulation points that meet the convergence condition is stored, including: Following the ordered simulation execution path, traverse all simulation points within the ordered simulation execution path: The current engine state parameter X( k ) and the current flight envelope environmental parameters U( k The input is fed into the aero-engine performance model to generate the model output Y( k ) and model residual e( k ),in, k For simulation points; Compare the residuals e( of the model) k The model residual e is compared with the preset convergence criterion ε and the result is used to determine the model residual e( k The convergence criterion ε is used as the convergence condition. If the convergence condition is met, proceed to state update and update the next engine state parameter X( k +1) Set to the new engine state parameter X obtained after convergence of the current simulation point. new ( k ); If the convergence condition is not met, enter state holding mode and set the next engine state parameter X( k +1) is set to the engine state parameter X input before the current simulation point calculation. k ); Store the model output Y( that satisfies the convergence condition) k ).

4. The full envelope control planning design method based on an aero-engine performance model according to claim 3, characterized in that, Also includes: If the number of times the state is maintained exceeds a preset threshold or the simulated value of the engine state parameter exceeds the physically valid range, a state rollback will be executed. The next engine state parameter X( k +1) Revert to the first simulation point in the ordered simulation execution path that satisfies the convergence condition under the current flight envelope environmental parameters. l Corresponding engine state parameter X new ( l ).

5. The full envelope control planning design method based on an aero-engine performance model according to any one of claims 1 to 4, characterized in that, Also includes: When performing simulation calculations on simulation points using the aforementioned aero-engine performance model, a loop tuner is set between the input and output of the aero-engine performance model. The loop tuner is based on a proportional-integral PI control architecture and is used to adjust the closed-loop zeros and poles of the system. The circuit tuner includes a designed circuit tuner and a non-designed circuit tuner.

6. The full envelope control planning design method based on an aero-engine performance model according to any one of claims 1 to 4, characterized in that, Also includes: The flight envelope environmental parameters include the environmental input altitude H and Mach number Ma; The engine status parameters include high-pressure rotor speed NH, low-pressure rotor speed NL, exhaust temperature T5, engine pressure ratio EPR, compressor pressure ratio πc, turbine pressure ratio πT, and bypass ratio BPR. The input parameters also include engine controllable input parameters, which include fuel flow rate Wf and exhaust nozzle area A8.

7. The full envelope control planning design method based on an aero-engine performance model according to any one of claims 1 to 4, characterized in that, Based on the model output, a full envelope control plan is generated, including: Extract the parameter dataset related to the target control plan from the model output. The parameter dataset includes control variables, flight envelope environmental parameters, and engine state parameters. Based on the parameter dataset, a functional relationship between the control quantity and the flight envelope environmental parameters and engine state parameters is established using a modeling method. ,in, u The output control quantity, Env This is the parameter vector of the flight envelope environmental parameters. Eng These are the parameters of the engine state parameters; If the control quantity u is linearly related to only one of the engine state parameters, the functional relationship is simplified to: or ,in, k The slope of a linear function. b g is the intercept of the linear function, and g() is the correction function; The simplified functional relationship is used as the control plan.

8. A full envelope control planning and design device based on an aero-engine performance model, characterized in that, include: The input parameter determination module is used to acquire input parameters and, based on the input parameters, generate a set of discrete simulation points covering the entire flight envelope and all engine operating conditions. The input parameters include the boundaries of the flight envelope environmental parameters and the simulation interval of the flight envelope environmental parameters, the boundaries of the engine state parameters and the simulation interval of the engine state parameters, and each simulation point is uniquely determined by a specific set of values ​​of the flight envelope environmental parameters and the engine state parameters. The simulation execution path generation module is used to set the minimum disturbance flight condition switching rules, sort the discrete simulation point set according to the minimum disturbance flight condition switching rules, and generate an ordered simulation execution path. The simulation module is used to initialize the aero-engine performance model, assign initial state parameters and initial inputs to the first simulation point in the ordered simulation execution path, perform simulation calculations on the simulation point through the aero-engine performance model, until all simulation points in the ordered simulation execution path are traversed, and store the model output of all simulation points that meet the convergence conditions. The control plan generation module is used to generate a full envelope control plan based on the model output.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the full envelope control plan design method based on the aero-engine performance model as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that executes the full envelope control plan design method based on the aero-engine performance model according to any one of claims 1 to 7.

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