Method for optimizing minimum fuel consumption performance of an aero-engine based on flight speed closed loop

Abstract

The present application belongs to the technical field of aero-engines, and specifically discloses a minimum fuel consumption performance optimization method for an aero-engine based on a flight speed closed loop, which constructs a combined closed loop architecture of the aero-engine, comprising a flight speed control closed loop, an engine rotating speed control closed loop and an optimization calculation loop.Taking the main fuel flow as an optimization index, the performance gradient is estimated on line through a symmetrical disturbance method, the nozzle area correction amount is updated by using the steepest descent method, and the actual nozzle area command is obtained in combination with the steady-state base value of the nozzle area.The method uses the easily measured parameter of flight speed to replace the difficult-to-directly-measure thrust information, reduces the dependence on high-precision models, realizes on-line optimization of the minimum fuel consumption target on the premise of ensuring the stability of the original closed loop, and is simple in engineering implementation and has good adaptability to the performance degradation of the whole life cycle of the engine.

Description

Technical Field

[0001] This invention belongs to the field of aero-engine technology, specifically relating to a method for optimizing the minimum fuel consumption performance of aero-engines based on a flight speed closed-loop. Background Technology

[0002] Aero engines are the core component of aircraft power plants, and their fuel economy directly affects an aircraft's range, endurance, and operational economics. With the increasing demands for energy conservation, emission reduction, and operational cost control in the air transport industry, further exploring the fuel-saving potential of engines while ensuring flight safety and engine reliability has become an important research direction in the field of aero engine control. Performance optimization control technology aims to shift the engine's operating point towards better overall performance by adjusting the engine's adjustable geometric parameters or control variables online, thereby reducing fuel consumption, extending engine life, or improving thrust response quality. This technology is of great significance for improving aircraft mission effectiveness and reducing life-cycle costs.

[0003] Currently, various performance optimization methods have been developed both domestically and internationally, including genetic algorithms, intelligent optimization algorithms, neural network methods, and model predictive optimization. These methods are typically based on high-precision engine component-level models or simplified performance models, using internal thermodynamic parameters such as thrust, fuel consumption rate, and turbine inlet temperature as optimization objectives or constraints. In engineering practice, engine control systems primarily perform closed-loop regulation based on parameters such as engine speed, temperature, and pressure ratio to ensure safety and stability throughout the entire flight envelope. Performance optimization serves as an additional functional layer, attempting to further improve fuel economy.

[0004] However, existing technologies still have the following problems: First, it is difficult to measure engine thrust with high precision in real time under airborne conditions. The fundamental reason is that during long-term engine service, performance degradation such as component wear, fouling, and aging is inevitable, leading to the failure of the nominal model and the deviation of the actual thrust characteristics from the model estimation. To accurately characterize the degradation state, the modeling cost is high, parameter identification is difficult, and continuous correction is required, resulting in high engineering complexity. If a fixed model is used, the thrust estimation accuracy will decrease significantly. In addition, some methods rely on parameters inside the engine that are difficult to measure directly as feedback, further making it difficult to implement online optimization based on thrust or internal parameter feedback. Second, most methods treat the engine as an isolated object, ignoring its closed-loop coupling with aircraft dynamics and flight control systems. The optimal point based on a single model may not represent the true optimal state under flight-engine coupling conditions. Summary of the Invention

[0005] The purpose of this invention is to solve the problem of the difficulty in implementing online optimization engineering based on thrust feedback in the prior art, and to propose a method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed loop.

[0006] The technical solution of this invention is: a method for optimizing the minimum fuel consumption performance of an aero-engine based on a closed-loop flight speed method, comprising: Step 1: Based on the constructed flight-engine joint closed-loop architecture, calculate the throttle command according to the target flight speed and the actual flight speed, determine the main fuel flow rate according to the throttle command, and obtain the steady-state base value of the nozzle area using the steady-state controller according to the current operating state of the aero-engine and flight conditions. Step 2: Using the main fuel flow rate as the optimization index and the nozzle area correction as the optimization variable, the local gradient is estimated by symmetric perturbation and central difference method. Based on the estimation result of the local gradient, the nozzle area correction is updated by the steepest descent update mechanism with constrained projection to obtain the nozzle area correction at the next moment. Step 3: Based on the nozzle area correction amount at the next moment and the steady-state base value of the nozzle area, obtain the actual nozzle area command, and repeat the above steps until the main fuel flow rate reaches the optimal value.

[0007] Preferably, the flight-engine joint closed-loop architecture includes: an aero-engine and a flight speed control closed loop, an engine speed control closed loop, and an optimization calculation loop connected to the aero-engine; The flight speed control closed loop is used to obtain throttle commands based on the target flight speed and the actual flight speed. The engine speed control closed loop is used to obtain the main fuel flow rate based on the throttle command and the current high-pressure rotor speed of the aero-engine, and output it to the aero-engine; The optimization calculation loop is used to output a nozzle area correction amount with the main fuel flow rate as the optimization index, and then apply the correction amount to the steady-state base value of the nozzle area to the aero-engine after correcting the nozzle area steady-state base value. The aero-engine outputs thrust based on the main fuel flow rate and the corrected nozzle area to drive the aircraft to generate a speed response.

[0008] Preferably, step 1 includes: Step 1.1: Construct the aforementioned joint closed-loop architecture for the aircraft and engine; Step 1.2: Based on the deviation between the target flight speed and the actual flight speed, obtain the throttle command through the speed closed-loop controller in the flight speed control closed loop; Step 1.3: Map the throttle command into the target speed of the high-pressure rotor of the aero-engine, and obtain the main fuel flow rate through the engine fuel controller in the engine speed control closed loop based on the deviation between the target speed of the high-pressure rotor and the current speed of the high-pressure rotor. Step 1.4: Based on the current rotational speed, flight altitude, and flight Mach number of the high-pressure rotor, obtain the steady-state base value of the nozzle area through the steady-state controller.

[0009] Preferably, step 2 includes: Step 2.1: Apply positive and negative symmetrical perturbations to the current nozzle area correction amount, and perform data buffering and time window mean calculation for the main fuel flow rate under each perturbation to obtain the quasi-steady-state performance estimate corresponding to the positive perturbation and the quasi-steady-state performance estimate corresponding to the negative perturbation; Step 2.2: Calculate the local gradient estimate based on the quasi-steady-state performance estimate corresponding to the positive disturbance and the quasi-steady-state performance estimate corresponding to the negative disturbance; Step 2.3: Based on the local gradient estimate and the preset optimization step size, update the nozzle area correction using the steepest descent update mechanism with constrained projection to obtain the nozzle area correction at the next moment.

[0010] Preferably, in step 2.1, data buffering and time window mean calculation are performed on the main fuel flow rate under each disturbance, including: The performance signal of the main fuel flow is collected in real time under each disturbance. The performance signal of the main fuel flow obtained by continuous sampling is recombined into a time window vector of length N. The arithmetic mean of the data in the time window vector is calculated as the quasi-steady-state performance estimate corresponding to the current disturbance.

[0011] Preferably, in step 2.2, the local gradient estimate is calculated according to the following formula: ; in, This is a local gradient estimate. This represents the estimated quasi-steady-state performance value corresponding to the positive disturbance. This represents the estimated quasi-steady-state performance value corresponding to the negative perturbation. This represents the disturbance amplitude.

[0012] Preferably, in step 2.3, the nozzle area correction amount at the next moment is calculated according to the following formula: ; in, for The amount of nozzle area correction at any given time. For interval projection operators, To represent the preset lower limit of the optimization variable, To represent the preset upper limit of the optimization variable, for The amount of nozzle area correction at any given time. To find the optimal step length, for The local gradient estimate at time t.

[0013] As a preferred option, the method for optimizing the minimum fuel consumption performance of an aero-engine based on a closed-loop flight speed also includes: real-time monitoring of key parameters of the aero-engine during the optimization process, and selective intervention in the optimization process based on the monitored values ​​of the key parameters and a preset limit protection mechanism.

[0014] Preferably, the limit protection mechanism includes: When the monitored values ​​of the key parameters of the aero-engine reach the preset safety boundary, the local gradient estimation value is limited, or the optimization step size is frozen and the update is paused, or it is rolled back to the nozzle area correction amount of the previous moment.

[0015] Preferably, the key parameters of the aero-engine include at least one of engine speed, turbine inlet temperature, surge margin, and fuel flow rate.

[0016] The beneficial effects of this invention are: This invention presents a closed-loop method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed, reducing reliance on high-precision independent engine models. Using flight speed as the outer feedback constraint and main fuel flow rate as the optimization index, it employs symmetrical perturbation and central difference methods to estimate performance gradients online. This eliminates the need for establishing engine thrust models or complex performance mapping relationships, effectively avoiding optimization failures caused by model mismatches due to performance degradation such as component wear, fouling, and aging. It also demonstrates stronger adaptability to performance changes throughout the engine's entire lifecycle. By using flight speed to replace thrust information, which is difficult to measure directly, and combining it with gradient descent for online optimization, it avoids the difficulties and high costs associated with acquiring thrust signals in airborne environments, significantly improving the method's engineering feasibility. Attached Figure Description

[0017] Figure 1 The diagram shows a flowchart of a method for optimizing the minimum fuel consumption performance of an aero-engine based on a closed-loop flight speed mechanism. Figure 2 The diagram shown is a schematic of a combined air-to-air and air-to-air closed-loop architecture. Figure 3 The diagram shows a closed-loop architecture for flight speed control based on the combined flight and engine. Figure 4 The figure shown is a schematic diagram of the simulation results of the joint control of the aircraft and the engine; Figure 5 The figure shown is a schematic diagram of the simulation results for optimizing the steady-state performance of the combined flight engine and generator. Detailed Implementation

[0018] 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.

[0019] This invention provides a method for optimizing the minimum fuel consumption performance of aero-engines based on a flight speed closed-loop. It introduces a performance optimization branch independent of the original main control channel into the flight-engine joint closed-loop system. This branch adds adjustments to the adjustable geometric parameters of the aero-engine, thereby achieving online minimum fuel consumption search without altering the basic structure of the flight speed closed-loop and the engine's main fuel control. The core of this method lies in unifying the flight speed control closed-loop, engine speed control closed-loop, and optimization calculation loop into a single flight-engine joint closed-loop architecture. In selecting feedback information, easily measurable parameters such as flight speed are used as the outer feedback constraint. In designing optimization variables, the adjustable geometric area of ​​the nozzle is used as an additional adjustable variable. In optimization implementation, data buffering, time window averaging, central difference gradient estimation, and a constrained projection steepest descent update mechanism are employed to achieve online performance optimization for the flight-engine coupled closed-loop system, thereby reducing fuel consumption while maintaining the original control stability.

[0020] Please see Figure 1 , Figure 1 The diagram shows a flowchart of a method for optimizing the minimum fuel consumption performance of an aero-engine based on a closed-loop flight speed mechanism. Figure 1 As shown, the method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop in this embodiment may include the following steps: Step 1: Based on the constructed flight-engine joint closed-loop architecture, calculate the throttle command according to the target flight speed and the actual flight speed, determine the main fuel flow rate according to the throttle command, and obtain the steady-state base value of the nozzle area using the steady-state controller according to the current operating state of the aero-engine and flight conditions.

[0021] Please see Figure 2 , Figure 2 The diagram shown is a schematic representation of a combined air-to-ground (ATO) closed-loop architecture. Figure 2As shown, the flight-engine integrated closed-loop architecture of this embodiment includes: an aero-engine and a flight speed control closed loop, an engine speed control closed loop, and an optimization calculation loop connected to the aero-engine. The flight speed control closed loop is used to obtain throttle commands based on the target flight speed and the actual flight speed; the engine speed control closed loop is used to obtain the main fuel flow rate based on the throttle command and the current high-pressure rotor speed of the aero-engine, and outputs it to the aero-engine; the optimization calculation loop is used to output a nozzle area correction amount using the main fuel flow rate as an optimization index, and applies it to the aero-engine after correcting the steady-state base value of the nozzle area based on the nozzle area correction amount; the aero-engine outputs thrust to drive the aircraft to generate a speed response based on the main fuel flow rate and the corrected nozzle area.

[0022] Specifically, in this embodiment, the flight speed control closed loop is based on the target flight speed. and actual flight speed The deviation between these parameters is used as input, and the speed closed-loop controller outputs a throttle command, i.e., the throttle lever angle (PLA). After command mapping, the throttle command is converted into the target rotational speed of the high-pressure rotor of the aero-engine. The engine's main fuel controller is based on the target speed of the high-pressure rotor. Current speed of the high-voltage rotor The deviation generates the main fuel flow Aero engines control the main fuel flow. The combined effect of the adjustable geometry of the nozzle and the output thrust This drives the aircraft to generate a speed response.

[0023] In this embodiment, step 1 may include the following steps: Step 1.1: Construct a joint closed-loop architecture for the aircraft and engine; Step 1.2: Based on the deviation between the target flight speed and the actual flight speed, the throttle command is obtained through the speed closed-loop controller in the flight speed control closed loop; Step 1.3: Map the throttle command to the target speed of the high-pressure rotor of the aero-engine. Based on the deviation between the target speed of the high-pressure rotor and the current speed of the high-pressure rotor, obtain the main fuel flow through the engine fuel controller in the engine speed control closed loop. Step 1.4: Based on the current high-pressure rotor speed, flight altitude, and flight Mach number, obtain the steady-state base value of the nozzle area through the steady-state controller.

[0024] Step 2: Using the main fuel flow rate as the optimization index and the nozzle area correction as the optimization variable, the local gradient is estimated by symmetric perturbation and central difference method. Based on the estimation results of the local gradient, the nozzle area correction is updated by the steepest descent update mechanism with constrained projection to obtain the nozzle area correction at the next time step.

[0025] In this embodiment, a nozzle area control method that combines the steady-state base value and the optimization correction is adopted. The original steady-state controller of the engine provides the steady-state base value of the adjustable geometric area of ​​the nozzle. Online output correction value of performance optimization loop The actual nozzle area command can be obtained by superimposing the two. This control method ensures that the original steady-state controller can maintain the component matching relationship and basic operating point, while the optimization loop is only used as an additional correction channel to adjust the adjustable geometric parameters.

[0026] Understandably, using Specific Fuel Consumption (SFC) as an optimization metric, given a fixed flight speed closed loop, can directly use the main fuel flow rate. As an optimization indicator, nozzle area correction amount As an optimization variable, the nozzle area correction is adjusted online to optimize the objective function. Minimize as much as possible under a given flight mission and closed-loop constraints.

[0027] In this embodiment, step 2 includes the following steps: Step 2.1: Apply positive and negative symmetrical perturbations to the current nozzle area correction amount, and perform data buffering and time window mean calculation for the main fuel flow rate under each perturbation to obtain the quasi-steady-state performance estimate corresponding to the positive perturbation and the quasi-steady-state performance estimate corresponding to the negative perturbation.

[0028] Specifically, in step 2.1, data buffering and time window mean calculation are performed on the main fuel flow rate under each type of disturbance, including: The performance signal of the main fuel flow is collected in real time under each disturbance. The performance signal of the main fuel flow obtained by continuous sampling is recombined into a time window vector of length N. The arithmetic mean of the data in the time window vector is calculated as the quasi-steady-state performance estimate corresponding to the current disturbance.

[0029] It should be noted that, considering the dynamic response, measurement fluctuations, and transient disturbances inherent in the joint closed-loop architecture, directly using instantaneous performance indicators for gradient estimation can easily lead to unstable gradient directions. Therefore, using data buffering and time window averaging to calculate the quasi-steady-state performance estimate under the current disturbance reduces the impact of high-frequency fluctuations and short-term transients on the optimization results, ensuring the stability and convergence of the optimization process.

[0030] Step 2.2: Calculate the local gradient estimate based on the quasi-steady-state performance estimate corresponding to the positive disturbance and the quasi-steady-state performance estimate corresponding to the negative disturbance.

[0031] Specifically, in step 2.2, the local gradient estimate is calculated according to the following formula: ; in, This is a local gradient estimate. This represents the estimated quasi-steady-state performance value corresponding to the positive disturbance. This represents the estimated quasi-steady-state performance value corresponding to the negative perturbation. This represents the disturbance amplitude.

[0032] In this embodiment, symmetric perturbation and central difference method are used to estimate the performance gradient online, by adjusting the current optimization variables. Apply positive and negative symmetrical perturbations to obtain quasi-steady-state performance estimates for the corresponding time window mean. and Based on this, the local gradient estimate is calculated. This method can obtain the local optimization direction without establishing an explicit analytical model of SFC or fuel flow with respect to the optimization variable.

[0033] Step 2.3: Based on the local gradient estimate and the preset optimization step size, the nozzle area correction is updated using the steepest descent update mechanism with constrained projection to obtain the nozzle area correction at the next moment.

[0034] Specifically, in step 2.3, the nozzle area correction for the next moment is calculated using the following formula: ; in, for The amount of nozzle area correction at any given time. For interval projection operators, To represent the preset lower limit of the optimization variable, To represent the preset upper limit of the optimization variable, for The amount of nozzle area correction at any given time. To find the optimal step length, for The local gradient estimate at time t.

[0035] In this embodiment, the interval projection operator is used. Constraints ensure that the nozzle area correction is always within an implementable range, improving the algorithm's engineering usability and operational safety.

[0036] Step 3: Based on the nozzle area correction amount and the nozzle area steady-state base value at the next moment, obtain the actual nozzle area command, and repeat the above steps until the main fuel flow rate reaches the optimal value.

[0037] Specifically, the actual nozzle area command can be obtained by superimposing the nozzle area correction amount at the next moment with the steady-state base value of the nozzle area.

[0038] It is worth noting that the method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop in this embodiment utilizes the flight speed control closed loop as an outer mission constraint to continuously adjust the throttle command to ensure that the aircraft speed is maintained near the target value; the engine speed control closed loop ensures the stability of the basic operating state of the aero-engine; and the optimization calculation loop, under the combined action of the above two closed loops, gradually pushes the aero-engine operating point towards the low fuel consumption region. Therefore, the optimization process is always carried out within the context of a real flight-engine coupled closed loop, rather than a static optimization of a single engine detached from flight mission conditions.

[0039] The embodiments of this invention fully consider the real working conditions of the flight-engine coupled closed loop, and integrate the flight speed control closed loop, the engine speed control closed loop, and the performance optimization calculation loop. The optimization process is always carried out under the combined effect of flight mission constraints and engine basic control stability. The obtained optimal operating point represents the real optimal point under the flight-engine joint closed loop condition. It is closer to the actual application scenario than offline optimization or open-loop optimization based on engine single model, and the optimization result has greater engineering value.

[0040] In a preferred embodiment, the method for optimizing the minimum fuel consumption performance of an aero-engine based on a closed-loop flight speed further includes: real-time monitoring of key parameters of the aero-engine during the optimization process, and selective intervention in the optimization process based on the monitored values ​​of the key parameters and a preset limit protection mechanism.

[0041] Specifically, the limit protection mechanism includes: when the monitored value of a key parameter of the aero-engine reaches a preset safety boundary, limiting the local gradient estimate, freezing the optimization step size and pausing updates, or reverting to the nozzle area correction amount of the previous moment. Optionally, the key parameters of the aero-engine include at least one of engine speed, turbine inlet temperature, surge margin, and fuel flow rate.

[0042] In this embodiment, by setting a limit protection mechanism during the online performance optimization process, the optimization variables, control commands, and key engine status parameters can be monitored and constrained in real time. When the engine speed, turbine inlet temperature, surge margin, fuel flow, or other key parameters are detected to be close to the preset safety boundary, the gradient update amount is immediately limited, the optimization step size is frozen, or the actual nozzle area command is rolled back. This ensures that the performance optimization process is always carried out within the engine's allowable operating envelope, thereby avoiding adverse effects of online optimization on the original flight speed control closed loop, engine speed control closed loop, and safety protection logic, and ensuring the safety, stability, and engineering feasibility of the system during the performance improvement process.

[0043] It should be noted that, in terms of implementation, the method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed loop in this embodiment can output environmental state quantities such as flight altitude and flight Mach number to the engine control system as input conditions for the engine gain scheduling controller or performance model; the optimization calculation loop is coupled with the engine speed control closed loop through signals such as fuel flow, speed, velocity and performance indicators.

[0044] Please see Figure 3 , Figure 3 The diagram shown illustrates a closed-loop architecture for flight speed control based on a combined flight engine and propulsion system. Figure 3 As illustrated, exemplarily, the speed closed-loop controller in the flight speed control closed loop can be a PID controller, the attitude closed loop can be a nonlinear dynamic inverse control method, and the engine main fuel controller can be a speed closed-loop controller. It is understood that the flight-engine joint closed-loop architecture of this embodiment is not limited to a specific controller form; as long as it can achieve unified coordination of the flight speed control closed loop, the engine speed control closed loop, and the optimization calculation loop with additional corrections, it falls within the protection scope of this invention.

[0045] The proposed method for optimizing the minimum fuel consumption performance of aero-engines based on a flight speed closed-loop reduces reliance on high-precision independent engine models. Using flight speed as the outer feedback constraint and main fuel flow rate as the optimization index, it employs symmetrical perturbation and central difference methods to estimate performance gradients online. This eliminates the need for establishing engine thrust models or complex performance mapping relationships, effectively avoiding optimization failures caused by model mismatches due to performance degradation from component wear, fouling, and aging. It also demonstrates stronger adaptability to performance changes throughout the engine's lifecycle. By using flight speed to replace thrust information, which is difficult to measure directly, and combining it with gradient descent for online optimization, the method avoids the difficulties and high costs associated with acquiring thrust signals in airborne environments, significantly improving its engineering feasibility.

[0046] It is understood that the method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop in this invention is not only applicable to scenarios where the adjustable geometric area of ​​the nozzle is used as the optimization variable and the fuel consumption rate is used as the optimization index, but can also be extended to online optimization problems of other adjustable geometric parameters (such as inlet guide vane angle, bleed valve opening, etc.) or other performance indicators (including but not limited to exhaust temperature, infrared signature intensity, etc.).

[0047] Furthermore, the effectiveness of the proposed method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop is illustrated through specific simulation examples.

[0048] A simulation system with a flight Mach number of 1.2 and a flight altitude of 11 km was constructed, using a cruise condition of Ma=1.2 and Alt=11 km. This system incorporates a flight speed control closed loop, an engine speed control closed loop, and an optimization calculation loop, forming a combined flight-engine closed-loop architecture. The flight speed control closed loop takes the error between the target flight speed and the actual flight speed as input. The speed controller generates throttle commands, which are then converted into the target high-pressure rotor speed of the aero-engine via a command mapping module. The engine's main fuel controller is based on the target speed of the high-pressure rotor. Current speed of the high-voltage rotor The deviation generates the main fuel flow .

[0049] Select nozzle area As the target for optimization, the engine's original steady-state controller provides the base value of the nozzle area. The performance optimizer calculates the area correction online. The two values ​​are then superimposed to obtain the actual nozzle area command. Using SFC as the optimization index, the continuously sampled performance signal is reconstructed using a buffer, and the mean value is calculated within a set time window as the quasi-steady-state performance estimate. Subsequently, positive and negative symmetrical small perturbations are applied to the current nozzle area correction, and the corresponding quasi-steady-state performance estimates before and after the perturbation, i.e., the average performance index, are obtained. The local gradient estimate is calculated using the central difference method, and then the steepest descent method combined with interval projection constraints is applied to... Iterative updates will be performed.

[0050] Please see Figure 4 , Figure 4 The diagram shown illustrates the simulation results of a combined flight and engine control system, illustrating the nozzle area under cruise conditions at a flight Mach number of 1.2 and an altitude of 11 km. Simulation results of the joint control of the engine and turbine under open-loop variation. Figure (a) shows the fuel consumption rate and estimated thrust as a function of... The characteristic plot of the open-loop change shows that... Under open-loop variation conditions, the fuel consumption rate response of the combined air-fuel system changes with... The change exhibits convex characteristics, and due to the presence of velocity closed-loop control, the thrust parameters of the combined propulsion and engine system can remain stable. Figure (b) shows the control quantity. The variation in fuel flow rate demonstrates the method used in this embodiment. The variation law was analyzed, and it was proven that under the speed closed-loop condition, fuel flow rate and fuel consumption rate exhibit similar convex characteristics. Therefore, in practical applications, fuel flow rate can be used to characterize the change in fuel consumption rate under the speed closed-loop condition. Figures (c) and (d) respectively show the controlled variable response curves of engine speed control and aircraft speed control, indicating that the control effect of the combined engine and flight system is good, providing a basis for subsequent steady-state performance optimization. From Figure 4 The simulation results show that, under this cruise condition, the SFC (Self-Fueled Capacitor) increases with nozzle area. The changes exhibit local convexity, providing a basis for using the gradient descent method to perform online performance optimization.

[0051] Please see Figure 5 , Figure 5 The figure shows a schematic diagram of the simulation results for the steady-state performance optimization of the combined flight and engine systems. It illustrates the simulation results under cruise conditions with a flight Mach number of 1.2 and a flight altitude of 11 km. Figure (a) shows the closed-loop optimization characteristics of fuel consumption rate and estimated thrust, indicating that under this condition, the combined system can maintain stable thrust while allowing the fuel consumption rate to gradually decrease to the optimal point. Figure (b) shows the control variables. The closed-loop characteristic diagram of fuel flow shows that the optimization system can adjust... The aircraft slowly descends to its optimum, and during this process, the closed-loop system can automatically adjust the fuel flow to reach a steady-state value. Figures (c) and (d) show the controlled variable response curves of engine speed control and aircraft speed control, respectively, indicating that after adding the performance optimization architecture, the flight control and engine control systems can still track the controlled variable target value well.

[0052] from Figure 5 The simulation results show that the nozzle area After several stepwise adjustments, it gradually converged to around 1.22, with the main fuel flow rate... A new equilibrium is then reached; throughout the optimization process, the actual flight speed The current speed of the high-voltage rotor remains close to the target value. The ability to stably track commands indicates that neither the flight speed control closed loop nor the engine speed control closed loop has been disrupted. Compared to the steady-state initial value, the method of this invention reduces fuel consumption by approximately 0.5%. Therefore, the minimum fuel consumption performance optimization method for aero-engines based on the flight speed closed loop of this invention can achieve online performance optimization oriented towards the minimum fuel consumption target within the context of a combined flight-engine closed loop, while also considering flight mission constraints and basic engine control stability, demonstrating promising engineering application prospects.

[0053] 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 method for optimizing the minimum fuel consumption performance of an aero-engine based on a closed-loop flight speed mechanism, characterized in that, include: Step 1: Based on the constructed flight-engine joint closed-loop architecture, calculate the throttle command according to the target flight speed and the actual flight speed, determine the main fuel flow rate according to the throttle command, and obtain the steady-state base value of the nozzle area using the steady-state controller according to the current operating state of the aero-engine and flight conditions. Step 2: Using the main fuel flow rate as the optimization index and the nozzle area correction as the optimization variable, the local gradient is estimated by symmetric perturbation and central difference method. Based on the estimation result of the local gradient, the nozzle area correction is updated by the steepest descent update mechanism with constrained projection to obtain the nozzle area correction at the next moment. Step 3: Based on the nozzle area correction amount at the next moment and the steady-state base value of the nozzle area, obtain the actual nozzle area command, and repeat the above steps until the main fuel flow rate reaches the optimal value.

2. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 1, characterized in that, The flight-engine joint closed-loop architecture includes: an aero-engine and a flight speed control closed loop, an engine speed control closed loop, and an optimization calculation loop connected to the aero-engine; The flight speed control closed loop is used to obtain the throttle command based on the target flight speed and the actual flight speed; The engine speed control closed loop is used to obtain the main fuel flow rate based on the throttle command and the current high-pressure rotor speed of the aero-engine, and output it to the aero-engine; The optimization calculation loop is used to output a nozzle area correction amount with the main fuel flow rate as the optimization index, and then apply the correction amount to the steady-state base value of the nozzle area to the aero-engine after correcting the nozzle area steady-state base value. The aero-engine outputs thrust based on the main fuel flow rate and the corrected nozzle area to drive the aircraft to generate a speed response.

3. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 2, characterized in that, Step 1 includes: Step 1.1: Construct the aforementioned joint closed-loop architecture for the aircraft and engine; Step 1.2: Based on the deviation between the target flight speed and the actual flight speed, obtain the throttle command through the speed closed-loop controller in the flight speed control closed loop; Step 1.3: Map the throttle command into the target speed of the high-pressure rotor of the aero-engine, and obtain the main fuel flow rate through the engine fuel controller in the engine speed control closed loop based on the deviation between the target speed of the high-pressure rotor and the current speed of the high-pressure rotor. Step 1.4: Based on the current rotational speed, flight altitude, and flight Mach number of the high-pressure rotor, obtain the steady-state base value of the nozzle area through the steady-state controller.

4. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 1, characterized in that, Step 2 includes: Step 2.1: Apply positive and negative symmetrical perturbations to the current nozzle area correction amount, and perform data buffering and time window mean calculation for the main fuel flow rate under each perturbation to obtain the quasi-steady-state performance estimate corresponding to the positive perturbation and the quasi-steady-state performance estimate corresponding to the negative perturbation; Step 2.2: Calculate the local gradient estimate based on the quasi-steady-state performance estimate corresponding to the positive disturbance and the quasi-steady-state performance estimate corresponding to the negative disturbance; Step 2.3: Based on the local gradient estimate and the preset optimization step size, update the nozzle area correction using the steepest descent update mechanism with constrained projection to obtain the nozzle area correction at the next moment.

5. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 4, characterized in that, In step 2.1, data buffering and time window mean calculation are performed on the main fuel flow rate under each disturbance, including: The performance signal of the main fuel flow is collected in real time under each disturbance. The performance signal of the main fuel flow obtained by continuous sampling is recombined into a time window vector of length N. The arithmetic mean of the data in the time window vector is calculated as the quasi-steady-state performance estimate corresponding to the current disturbance.

6. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 4, characterized in that, In step 2.2, the local gradient estimate is calculated according to the following formula: ； in, This is a local gradient estimate. This represents the estimated quasi-steady-state performance value corresponding to the positive disturbance. This represents the estimated quasi-steady-state performance value corresponding to the negative perturbation. This represents the disturbance amplitude.

7. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 4, characterized in that, In step 2.3, the nozzle area correction amount at the next moment is calculated according to the following formula: ； in, for The amount of nozzle area correction at any given time. For interval projection operators, To represent the preset lower limit of the optimization variable, To represent the preset upper limit of the optimization variable, for The amount of nozzle area correction at any given time. To find the optimal step length, for The local gradient estimate at time t.

8. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 1, characterized in that, Also includes: During the optimization process, the key parameters of the aero-engine are monitored in real time, and the optimization process is selectively intervened based on the monitored values ​​of the key parameters and the preset limit protection mechanism.

9. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 8, characterized in that, The extreme protection mechanism includes: When the monitored values ​​of the key parameters of the aero-engine reach the preset safety boundary, the local gradient estimation value is limited, or the optimization step size is frozen and the update is paused, or it is rolled back to the nozzle area correction amount of the previous moment.

10. The method for optimizing the minimum fuel consumption performance of aero-engines based on flight speed closed-loop as described in claim 8, characterized in that, The key parameters of the aero-engine include at least one of engine speed, turbine inlet temperature, surge margin, and fuel flow rate.

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