Integrated performance evaluation method based on aircraft and engine integrated parameter design

Abstract

This invention discloses a comprehensive performance evaluation method based on integrated parameter design of aircraft and engines, belonging to the field of aircraft design optimization and performance evaluation. This method addresses the problems of process fragmentation, insufficient simulation accuracy, and lack of a scientific and comprehensive evaluation system caused by the traditional separate design of aircraft and engines. Key technical points include: establishing aircraft load constraint analysis to determine feasible design space; calculating weight changes and maximum takeoff weight through a mission profile fuel consumption model and evaluating aircraft aerodynamic performance; determining the design parameters of key engine components based on thrust demand iteration and calculating their design point and non-design point performance; constructing an index system database at the mission layer, capability layer, and index layer; and finally, conducting an integrated comprehensive performance evaluation based on fuzzy hierarchical analysis. This invention achieves collaborative design and quantitative evaluation of aircraft and engine parameters, providing a basis for overall aircraft performance optimization.

Description

Technical Field

[0001] This invention belongs to the field of aircraft design optimization and performance evaluation technology, and particularly relates to a comprehensive performance evaluation method based on integrated parameter design of aircraft and engines. Background Technology

[0002] As aviation technology evolves towards higher efficiency, longer endurance, and multi-mission adaptability, the integrated design of aircraft and propulsion systems has become crucial for improving overall performance. In traditional design, the development processes of aircraft platforms and engines are relatively independent, making it difficult to achieve global optimization of parameters selected in the initial design phase across the entire mission profile. While conventional constraint analysis can initially define the design space during the conceptual design phase, its failure to effectively correlate with the detailed component characteristics of the engine and non-design point performance leads to biases in subsequent mission analysis, weight prediction, and performance calculations. Furthermore, existing evaluation methods are often limited to disciplinary or single-level indicators, lacking a comprehensive performance evaluation system that can systematically weigh multi-dimensional performance aspects such as aerodynamics, propulsion, weight, and energy management, making it difficult to scientifically and quantitatively evaluate and optimize integrated design schemes.

[0003] Although multidisciplinary design optimization methods have made significant progress in the aerospace field, existing research largely focuses on the synergistic optimization of aerodynamics and structure, and has not yet formed a design evaluation system that can connect top-level aircraft requirements, engine component parameters, non-design point performance, and overall system effectiveness. Data transfer between design modules still relies on manual intervention, resulting in low efficiency in design iteration and difficulty in accurately predicting integrated flight-engine performance at the conceptual stage. This technological gap severely restricts further improvements in the overall performance of aircraft. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a comprehensive performance evaluation method based on integrated parameter design of aircraft and engines, thereby resolving the issues present in the prior art.

[0005] In a first aspect, to achieve the above objectives, the present invention provides a comprehensive performance evaluation method based on integrated parameter design of aircraft and engine, comprising the following steps: S1. Based on the performance requirements of the aircraft conceptual design phase, establish constraint analysis to determine the feasible design space including thrust-to-weight ratio and wing loading; S2. By establishing a fuel consumption model for each stage of the complete mission profile of the aircraft, the weight change history of the aircraft is calculated and the maximum takeoff weight is determined. Then, the wing area and engine thrust are calculated, and the aerodynamic performance of the aircraft is evaluated based on this. S3. Based on the thrust requirements and flight conditions determined in S2, the design parameters of key engine components are determined through iterative calculations, and the engine performance at design points and non-design points is calculated. S4. Construct a database of aircraft and engine indicator systems that includes mission layer, capability layer and indicator layer, and conduct a comprehensive performance evaluation based on the calculation results of S1 to S3 through the indicator system.

[0006] Optionally, in S1, the constraint analysis includes: Based on the constraints of takeoff distance, sustained turn performance, and landing distance, a functional relationship between thrust-weight ratio and wing loading is established; the boundary curves of each constraint in the wing loading-thrust-weight ratio coordinate system are solved to form the constraint boundaries, and the minimum thrust-weight ratio requirement is determined by finding the upper envelope of each constraint curve.

[0007] Optionally, in S2, calculating the aircraft's weight change history and determining the maximum takeoff weight includes: The flight mission is broken down into multiple consecutive phases, including takeoff, climb, and cruise. For each phase, the fuel weight fraction is calculated based on dynamic pressure, speed, time, aerodynamic parameters, and propulsion system parameters. The weight change ratio throughout the mission is obtained by multiplying the fuel weight fractions of all phases, and the maximum takeoff weight is calculated by combining the empty weight and the payload weight.

[0008] Optionally, in S2, evaluating aircraft aerodynamic performance includes: Based on the determined engine thrust and wing area, a physical model is constructed that includes the aircraft weight, thrust, friction coefficient, and air density; the aerodynamic performance indicators of the aircraft during takeoff, acceleration, and climb are calculated, including takeoff distance, acceleration time, and climb rate.

[0009] Optionally, in S3, the design parameters of key engine components are determined through iterative calculations, including: Calculate the thrust coefficient based on the given flight altitude, Mach number, and thrust requirement to determine the maximum thrust requirement; iterate through the parameter combinations of low-pressure compressor pressure ratio, high-pressure compressor pressure ratio, and turbine inlet temperature, call the engine performance calculation function to evaluate the thrust and check whether the turbine outlet Mach number is less than the preset threshold; return the first parameter combination that satisfies the thrust requirement and aerodynamic constraints.

[0010] Optionally, in S3, calculating engine performance at design and non-design points includes: Based on the determined engine design parameters, calculate the reference operating state parameters and correction coefficients of temperature, pressure, and flow rate of the high and low pressure compressors and turbines at the design point; under given non-design point altitude, Mach number, and flow rate parameters, perform intake duct performance calculation and engine state iterative calculation, and output the performance parameters of each component.

[0011] Optionally, building a database of aircraft and engine performance indicators includes: Create a core data table containing fields for indicator name, parent level, self level, and top-level task name to define a three-layer structure of task layer, capability layer, and indicator layer; populate the database with preset seed data, and interactively supplement and verify the completeness of missing indicator data.

[0012] Optionally, in S4, the comprehensive performance evaluation includes: A hierarchical model containing a target layer, a criterion layer, and a scheme layer is constructed; a fuzzy judgment matrix is ​​constructed using triangular fuzzy numbers, and the fuzzy weights of each criterion are calculated; a comprehensive evaluation result is obtained through fuzzy weighted summation, and after defuzzification and consistency verification, a comprehensive performance score is output.

[0013] In a second aspect, the present invention also provides a computer terminal device, comprising: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the integrated performance evaluation method based on integrated aircraft and engine parameter design in the first aspect described above.

[0014] Thirdly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the integrated performance evaluation method based on integrated parameter design of aircraft and engine in the first aspect described above.

[0015] Compared with the prior art, the present invention has the following advantages and technical effects: This invention provides a comprehensive performance evaluation method based on integrated parameter design of aircraft and engines. By establishing an integrated process encompassing aircraft load constraint analysis, aircraft mission and performance calculation, engine design requirement decomposition and performance calculation, and comprehensive performance evaluation, it effectively solves the problem of process fragmentation caused by the traditional separate design of aircraft and engines. This method achieves a direct correlation and data closure between top-level aircraft requirements and engine component parameters, enabling the design points determined in the conceptual design phase to approach the global optimum under the full mission profile. By establishing a refined mission fuel consumption model and an engine non-design point performance model, the prediction accuracy of aircraft weight, range, and performance is significantly improved. The constructed three-level database (mission layer, capability layer, and indicator layer) and fuzzy hierarchical analysis evaluation system provide a scientific and quantifiable multi-dimensional evaluation method for the comprehensive performance of aircraft and engines, supporting the transformation of design decisions from experience-based judgment to model-driven approaches, thereby improving the overall performance optimization capability and efficiency of the aircraft. Attached Figure Description

[0016] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of the aircraft and engine indicator system according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the aircraft load constraint analysis process according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the maximum takeoff weight calculation process according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the design requirement decomposition and calculation process according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the engine design point calculation process according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the database program flow according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the comprehensive performance evaluation process according to an embodiment of the present invention; Figure 8 This is a schematic diagram illustrating the definition of comprehensive performance evaluation weights for different models in an embodiment of the present invention. Detailed Implementation

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0018] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0019] Example 1 like Figure 2-8 As shown, this embodiment provides a comprehensive performance evaluation method based on integrated parameter design of aircraft and engine, including: S1. Based on the performance requirements of the aircraft conceptual design phase, establish constraint analysis to determine the feasible design space including thrust-to-weight ratio and wing loading; S2. By establishing a fuel consumption model for each stage of the complete mission profile of the aircraft, the weight change history of the aircraft is calculated and the maximum takeoff weight is determined. Then, the wing area and engine thrust are calculated, and the aerodynamic performance of the aircraft is evaluated based on this. S3. Based on the thrust requirements and flight conditions determined in S2, the design parameters of key engine components are determined through iterative calculations, and the engine performance at design points and non-design points is calculated. S4. Construct a database of aircraft and engine indicator systems that includes mission layer, capability layer and indicator layer, and conduct a comprehensive performance evaluation based on the calculation results of S1 to S3 through the indicator system.

[0020] Furthermore, in S1, the constraint analysis includes: Based on the constraints of takeoff distance, sustained turn performance, and landing distance, a functional relationship between thrust-weight ratio and wing loading is established; the boundary curves of each constraint in the wing loading-thrust-weight ratio coordinate system are solved to form the constraint boundaries, and the minimum thrust-weight ratio requirement is determined by finding the upper envelope of each constraint curve.

[0021] Specifically, the implementation process of this embodiment includes: Establish an aircraft load constraint analysis module. During the aircraft conceptual design phase, this is achieved by establishing the aircraft thrust load ( ) and wing loading ( The matching relationship between the two factors determines the feasible design space. This pattern is based on the following formula: ; In the formula, Let g be the acceleration due to gravity. The above equation can be expressed as follows: and The functional relationship can be transformed into different expressions in different flight segments of the aircraft, thus converting to... and The corresponding boundaries in the constraint diagram. Based on this, the module, according to the performance indicators of each mission phase, including takeoff distance constraints, sustained turn performance constraints, and landing distance constraints, transforms each constraint condition into a functional relationship between thrust-to-weight ratio and wing loading. By solving the boundary curves of these equations in the coordinate system, the constraint boundaries surrounding the feasible design region can be formed. Finally, by finding the upper envelope of each constraint curve, the minimum thrust-to-weight ratio requirement that satisfies all performance requirements is determined, and the final design point is selected within the design feasible region, providing a basis for engine selection and key parameter design.

[0022] Furthermore, in S2, calculating the aircraft's weight change history and determining the maximum takeoff weight includes: The flight mission is broken down into multiple consecutive phases, including takeoff, climb, and cruise. For each phase, the fuel weight fraction is calculated based on dynamic pressure, speed, time, aerodynamic parameters, and propulsion system parameters. The weight change ratio throughout the mission is obtained by multiplying the fuel weight fractions of all phases, and the maximum takeoff weight is calculated by combining the empty weight and the payload weight.

[0023] Specifically, the implementation process of this embodiment includes: An aircraft mission analysis module was established. By creating mathematical models of fuel consumption at each stage of the complete mission profile, the key processes for calculating weight change history and determining maximum takeoff weight were calculated. The aircraft's takeoff weight ( It consists of three parts, including the payload ( Aircraft empty weight ( ) and weight of aviation kerosene ( ): ; The change in the aircraft's weight during flight is represented as follows: ; In the formula, This indicates the amount of fuel the aircraft had when it terminated a certain flight segment. This indicates the amount of fuel the aircraft had at the start of a certain flight segment. This is to determine the fuel consumption rate during installation.

[0024] This module breaks down the flight mission into multiple consecutive phases, including takeoff warm-up, takeoff acceleration, and takeoff. For each phase, it calculates the fuel weight fraction based on dynamic pressure, speed, time, aerodynamic parameters, and propulsion system parameters.

[0025] The takeoff phase can be divided into three stages: warm-up, acceleration, and takeoff. The changes in aircraft weight during warm-up are as follows: ; In the formula, This is the fuel consumption constant. For temperature ratio, This refers to the takeoff time.

[0026] The change in aircraft weight during acceleration is as follows: ; In the formula, For takeoff speed, is the coefficient of friction.

[0027] ; The change in aircraft weight during takeoff is represented as follows: ; By multiplying the fuel weight fractions at all stages, the weight change ratio throughout the mission is obtained. Combined with the empty weight and payload weight, the maximum takeoff weight is finally calculated.

[0028] Get the maximum takeoff weight ( After that, the engine is equipped with thrust ( The area of ​​the aircraft wing (S) and the area of ​​the aircraft wing are derived from the following formula: ; After determining the engine thrust and wing area, a physical model is constructed based on parameters such as aircraft weight, thrust, friction coefficient, and air density. This model is then used to calculate the aircraft's aerodynamic performance indicators at different flight phases (such as takeoff and cruise). Numerical integration methods are employed to obtain key performance data such as takeoff distance, acceleration time, and climb rate. Based on these results, the aircraft's aerodynamic efficiency, maximum climb performance, and acceleration capability are systematically evaluated, providing quantitative data for overall aircraft design and mission analysis.

[0029] Furthermore, in S2, the evaluation of aircraft aerodynamic performance includes: Based on the determined engine thrust and wing area, a physical model is constructed that includes the aircraft weight, thrust, friction coefficient, and air density; the aerodynamic performance indicators of the aircraft during takeoff, acceleration, and climb are calculated, including takeoff distance, acceleration time, and climb rate.

[0030] Specifically, the implementation process of this embodiment includes: After establishing an aircraft performance calculation module and obtaining the maximum takeoff weight... The engine thrust and aircraft wing area can be obtained from the following formula: ; After determining the engine thrust and wing area, a physical model is constructed based on parameters such as aircraft weight, thrust, friction coefficient, and air density. This model is then used to calculate the aircraft's aerodynamic performance indicators at different flight phases (such as takeoff and cruise). By setting reasonable lift-drag characteristic parameters and employing numerical integration methods, key performance data on takeoff distance are obtained. Based on these results, the aircraft's aerodynamic efficiency, maximum climb performance, and acceleration capability can be systematically evaluated, providing quantitative basis for overall aircraft design and mission analysis.

[0031] Furthermore, in S3, the design parameters of key engine components are determined through iterative calculations, including: Calculate the thrust coefficient based on the given flight altitude, Mach number, and thrust requirement to determine the thrust requirement; iterate through the parameter combinations of low-pressure compressor pressure ratio, high-pressure compressor pressure ratio, and turbine inlet temperature, call the engine performance calculation function to evaluate the thrust and check whether the turbine outlet Mach number is less than the preset threshold; return the first parameter combination that satisfies the thrust requirement and aerodynamic constraints.

[0032] Specifically, the implementation process of this embodiment includes: An engine design requirements decomposition module was established. The core task of this module is to determine the design parameters of key engine components through iterative calculations under given flight conditions and thrust requirements. The module first calculates the thrust coefficient based on the input design point flight altitude and Mach number to determine the required thrust of the engine. Then, using three key parameters—low-pressure compressor ratio, high-pressure compressor ratio, and turbine inlet temperature—it calls engine performance calculation functions to evaluate thrust for each parameter combination and checks whether the turbine exit Mach number meets the constraint condition (less than 0.8). When the first design point that simultaneously meets the thrust requirement (calculated thrust greater than required thrust) and aerodynamic constraints is found, the module immediately returns the parameters, including low-pressure compressor ratio, high-pressure compressor ratio, turbine pressure ratio, and turbine inlet temperature. If no feasible solution is found after traversing all parameter combinations, a design failure is indicated. This module lays the foundation for subsequent detailed engine design and characteristic analysis.

[0033] Furthermore, in S3, the calculation of engine performance at the design point and non-design point includes: Based on the determined engine design parameters, calculate the reference operating state parameters and correction coefficients of temperature, pressure, and flow rate of the high and low pressure compressors and turbines at the design point; under given non-design point altitude, Mach number, and flow rate parameters, perform intake duct performance calculation and engine state iterative calculation, and output the performance parameters of each component.

[0034] Specifically, the implementation process of this embodiment includes: An engine design point performance calculation module is established. This module is used to perform performance analysis at the engine design point. Based on the user-input parameters such as engine speed, flow rate, and compressor and turbine β values, combined with the results from the engine design requirement decomposition module, it calculates reference operating state parameters and correction coefficients (flow rate, pressure ratio, and efficiency) for the high- and low-pressure compressors and turbines. The calculation process is as follows: First, based on the operating points, bypass ratio, flow rates, and other parameters of each component at the design point, the state parameters of each node of the engine are solved according to the mathematical models of each component in the gas flow sequence. Second, the original characteristic curves are scaled based on the operating points of the fan, high-pressure compressor, turbine, and low-pressure turbine at the design point to provide a data foundation for the subsequent steady-state verification stage.

[0035] A non-design point performance calculation module for the engine was established. Based on given altitude and Mach number, flow parameters, combustor parameters, and iterative control parameters, and combined with the results of the preceding modules—engine design, design point calculation, constraint analysis, and mission analysis—it performs inlet performance calculations and engine state iterative calculations to derive key performance indicators such as engine mass, cooling airflow requirements, power extraction at takeoff, and emissions index. This helps in evaluating the engine's performance under different flight missions. Comprehensive calculations yield the engine's weight characteristics, cooling system requirements, and power extraction capabilities, providing crucial engineering decision-making support for overall engine design, performance optimization, and system integration.

[0036] Furthermore, the construction of a database of aircraft and engine performance indicators includes: Create a core data table containing fields for indicator name, parent level, self level, and top-level task name to define a three-layer structure of task layer, capability layer, and indicator layer; populate the database with preset seed data, and interactively supplement and verify the completeness of missing indicator data.

[0037] Specifically, the implementation process of this embodiment includes: Establish a database module for aircraft and engine performance indicators, such as... Figure 1 As shown, the aircraft and engine performance index database constructs a multi-level index system with task, capability, and index layers. Through database technology, it systematically manages the various requirements and evaluation indicators of aircraft and engine design tasks. The index system divides the various design tasks of aircraft and engines into different levels, each representing different design objectives and evaluation standards. This ensures that all tasks throughout the design process are clearly aligned with actual performance indicators, thereby providing support for design decisions.

[0038] Database initialization and table structure creation: Create a database file and establish at least one core data table within it. The core data table contains the following fields: metric_name is used to store the name of the metric or capability layer; `parent_layer` is used to store the name of the direct parent layer of this data item to define the hierarchical relationship; The metric_layer is used to identify the hierarchical attribute of the data item itself, and its values ​​include "task layer", "capability layer" or "metric layer". `root_task` stores the name of the top-level task to identify the top-level task hierarchy to which this data item belongs. Through the above process, a three-tiered indicator system is constructed: 1) Task layer The mission layer is the top layer of the system, primarily used to define aircraft missions. Each mission represents a specific flight mission type. Within the mission layer, different missions are further divided into lower-level capability layers and indicator layers according to their mission requirements. This layer is mainly used to set the overall design direction, such as the nature, purpose, and main objectives of the mission, providing a basic framework for aircraft performance evaluation.

[0039] 2) Capability layer The capability layer is a subset of the mission layer, describing the various capabilities and performance required to complete a mission. These capabilities reflect the main functional requirements of an aircraft when performing a specific mission.

[0040] The capability layer structure helps developers clearly define the different performance dimensions required for a task, and the performance parameters under each capability layer can be optimized under various operating conditions. This division of capability layer data allows the design team to perform detailed optimization and analysis based on each capability module.

[0041] 3) Indicator layer The metrics layer is the most granular data layer, specifically containing quantifiable metrics for aircraft and engine performance. It represents the concretization and quantification of the capability layer, providing detailed performance data required for mission achievement. These metrics not only provide quantitative data for design but also offer direct feedback for mission optimization.

[0042] The data for each indicator layer will revolve around the capability layer, and each indicator will be assigned relevant units, weights, and attributes such as whether smaller is better. This layer's design facilitates detailed calculations and comparisons of various performance indicators for aircraft and engines, enabling multi-dimensional evaluation. This layered design decomposes the complexity of aircraft and engines layer by layer, providing a foundation for subsequent data analysis.

[0043] Hierarchical data population begins with the database being populated using pre-set seed data. This seed data includes typical missions of the aircraft and the capability requirements and metrics for each mission. During the data population process, the program inserts the corresponding capabilities and metrics based on the needs of different missions. If some metric data is not fully populated during initialization, the system will display an input box in the graphical interface, prompting the user to manually fill in the missing metric data. After the user completes the input, the data will be automatically added to the database, ensuring data integrity and consistency.

[0044] Data integrity verification: For a given top-level task, by comparing the predefined complete list of indicators with the indicator names actually stored in the core data table, the system checks and identifies the missing indicator data that was preset but not successfully filled.

[0045] Interactive data supplementation: If missing indicator data is identified, a dialog box with input prompts is dynamically generated by calling the graphical user interface library to receive the parameter values ​​entered by the user for each missing indicator data; the parameter values ​​submitted by the user are updated as new records in the core data table to ensure data integrity.

[0046] Visual verification of hierarchical relationships: All data is queried and extracted from the core data table. Based on the parent-child relationship defined by the parent_layer and metric_name fields, a tree-like logical structure with the top-level task as the root node is constructed. The tree structure is printed out in the form of indented text on the console or rendered through a graphical interface to intuitively display and verify the completeness and hierarchical correctness of the entire indicator system from the task layer to the capability layer and then to the indicator layer.

[0047] Furthermore, in S4, the comprehensive performance evaluation includes: A hierarchical model containing a target layer, a criterion layer, and a scheme layer is constructed; a fuzzy judgment matrix is ​​constructed using triangular fuzzy numbers, and the fuzzy weights of each criterion are calculated; a comprehensive evaluation result is obtained through fuzzy weighted summation, and after defuzzification and consistency verification, a comprehensive performance score is output.

[0048] Specifically, the implementation process of this embodiment includes: Establish a comprehensive energy efficiency evaluation system for aircraft and engines. Based on the calculation results of the aforementioned modules, conduct a comprehensive energy efficiency evaluation according to the indicator system, calculate the final comprehensive efficiency score, and provide a quantitative basis for the matching optimization of aircraft and engines and the overall performance evaluation. The steps are as follows: like Figure 3 The following are the definitions of the overall performance evaluation weights for different models: In civil aviation passenger and cargo operations, the system focuses on two core directions: economy and reliability. Passenger aircraft prioritize fuel economy, range efficiency, and passenger comfort, while emphasizing aerodynamic efficiency and environmental noise control. Transport aircraft, on the other hand, emphasize a balance between high payload, long range, and short takeoff and landing performance, highlighting mission adaptability and operational stability. Together, they constitute a comprehensive paradigm for balancing economy, environment, and safety in civil aviation operations.

[0049] Hydrogen-powered passenger and cargo transport represents a new direction for energy transformation and sustainable development in civil aviation. In these missions, hydrogen-powered passenger aircraft are designed with a focus on "zero carbon emissions, high energy efficiency, and comfort," emphasizing efficient energy conversion through a hybrid propulsion system combining hydrogen fuel cells and gas turbines, as well as the safety of hydrogen storage and thermal management. While meeting long-range flight requirements, they optimize noise and emissions performance to achieve green civil aviation operations. Hydrogen-powered cargo aircraft, on the other hand, prioritize the energy density utilization and stability of the hydrogen system, enhancing structural load-bearing capacity and hydrogen tank layout efficiency to ensure energy economy and maintenance reliability under high load and long-range conditions. Their design emphasizes the synergistic optimization of energy supply, cargo mission support, and operating costs, representing a crucial development direction for hydrogen-powered aviation engineering.

[0050] Fuzzy pairwise comparison judgment matrix: In fuzzy hierarchical analysis, the elements of the pairwise comparison judgment matrix are represented by fuzzy numbers. Assuming there are n factors, decision-makers construct a fuzzy judgment matrix A by comparing the relative importance of these factors, where each element is a fuzzy number, typically a triangular fuzzy number (a, b, c), where a is the minimum value (representing the weakest preference), b is the most likely value (representing the most probable preference), and c is the maximum value (representing the strongest preference). The fuzzy judgment matrix A is shown below: ; Fuzzy weight calculation: By performing fuzzy synthesis on the fuzzy judgment matrix, the fuzzy weights of each criterion or scheme are calculated. Assume there are several decision-making levels. There are 1 criterion, and the fuzzy judgment matrix is ​​A. The weight of each criterion is 1. To calculate the weights, the fuzzy weights of each criterion can be obtained by normalizing the fuzzy judgment matrix. A common normalization method is to normalize each column vector so that the sum of all weights is 1.

[0051] ; In the formula, It is a standard The fuzzy weights are the criteria. The judgment value (based on fuzzy number weighting).

[0052] Fuzzy synthesis: The final comprehensive evaluation matrix is ​​obtained by fuzzy weighted summation. For example, for scheme j, the fuzzy comprehensive evaluation result is: ; In the formula, It is the comprehensive evaluation value of scheme j.

[0053] Deblurring process: After obtaining the fuzzy comprehensive evaluation results, it is usually necessary to defuzzify the fuzzy numbers in order to obtain a definite value.

[0054] The center value method is the most commonly used deblurring method. It takes the center value of the triangular fuzzy number as the final deblurring result. : .

[0055] Consistency check: To ensure the validity of the judgment matrix, a consistency check must be performed. First, the largest eigenvalue of the judgment matrix is ​​calculated, and then the consistency index (CI) is calculated: ; In the formula, n is the order of the matrix. Next, the consistency ratio CR is calculated: ; Here, RI is the random consistency index, and its value depends on the order n of the matrix. If CR ≤ 0.1, the judgment matrix is ​​consistent; otherwise, the judgment matrix needs to be re-evaluated.

[0056] Perform decision calculations: Ultimately, by comparing the defuzzification values ​​of each solution, the optimal solution can be determined, with solutions having larger weight values ​​indicating better decision results.

[0057] Example 2 In this embodiment, a computer terminal device is provided, including: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the comprehensive performance evaluation method based on the integrated parameter design of aircraft and engine described above.

[0058] In this embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the above-described integrated performance evaluation method based on integrated parameter design of aircraft and engine.

[0059] This invention provides a comprehensive performance evaluation method based on integrated parameter design of aircraft and engines. By establishing an integrated process encompassing aircraft load constraint analysis, aircraft mission and performance calculation, engine design requirement decomposition and performance calculation, and comprehensive performance evaluation, it effectively solves the problem of process fragmentation caused by the traditional separate design of aircraft and engines. This method achieves a direct correlation and data closure between top-level aircraft requirements and engine component parameters, enabling the design points determined in the conceptual design phase to approach the global optimum under the full mission profile. By establishing a refined mission fuel consumption model and an engine non-design point performance model, the prediction accuracy of aircraft weight, range, and performance is significantly improved. The constructed three-level database (mission layer, capability layer, and indicator layer) and fuzzy hierarchical analysis evaluation system provide a scientific and quantifiable multi-dimensional evaluation method for the comprehensive performance of aircraft and engines, supporting the transformation of design decisions from experience-based judgment to model-driven approaches, thereby improving the overall performance optimization capability and efficiency of the aircraft.

[0060] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating the overall performance based on the integrated parameters of the aircraft and engine, characterized in that, Includes the following steps: S1. Based on the performance requirements of the aircraft conceptual design phase, establish constraint analysis to determine the feasible design space including thrust-to-weight ratio and wing loading; S2. By establishing a fuel consumption model for each stage of the complete mission profile of the aircraft, the weight change history of the aircraft is calculated and the maximum takeoff weight is determined. Then, the wing area and engine thrust are calculated, and the aerodynamic performance of the aircraft is evaluated based on this. S3. Based on the thrust requirements and flight conditions determined in S2, the design parameters of key engine components are determined through iterative calculations, and the engine performance at design points and non-design points is calculated. S4. Construct a database of aircraft and engine indicator systems that includes mission layer, capability layer and indicator layer, and conduct a comprehensive performance evaluation based on the calculation results of S1 to S3 through the indicator system.

2. The method according to claim 1, characterized in that, In S1, establishing constraint analysis includes: Based on the constraints of takeoff distance, sustained turn performance, and landing distance, a functional relationship between thrust-weight ratio and wing loading is established; the boundary curves of each constraint in the wing loading-thrust-weight ratio coordinate system are solved to form the constraint boundaries, and the minimum thrust-weight ratio requirement is determined by finding the upper envelope of each constraint curve.

3. The method according to claim 1, characterized in that, In S2, calculating the aircraft's weight change history and determining the maximum takeoff weight includes: The flight mission is broken down into multiple consecutive phases, including takeoff, climb, and cruise. For each phase, the fuel weight fraction is calculated based on dynamic pressure, speed, time, aerodynamic parameters, and propulsion system parameters. The weight change ratio throughout the mission is obtained by multiplying the fuel weight fractions of all phases, and the maximum takeoff weight is calculated by combining the empty weight and the payload weight.

4. The method according to claim 1, characterized in that, In S2, evaluating aircraft aerodynamic performance includes: Based on the determined engine thrust and wing area, a physical model is constructed that includes the aircraft weight, thrust, friction coefficient, and air density; the aerodynamic performance indicators of the aircraft during takeoff, acceleration, and climb are calculated, including takeoff distance, acceleration time, and climb rate.

5. The method according to claim 1, characterized in that, In S3, the design parameters of key engine components are determined through iterative calculations, including: Calculate the thrust coefficient based on the given flight altitude, Mach number, and thrust requirement to determine the maximum thrust requirement; iterate through the parameter combinations of low-pressure compressor pressure ratio, high-pressure compressor pressure ratio, and turbine inlet temperature, call the engine performance calculation function to evaluate the thrust and check whether the turbine outlet Mach number is less than the preset threshold; return the first parameter combination that satisfies the thrust requirement and aerodynamic constraints.

6. The method according to claim 1, characterized in that, In S3, calculating engine performance at design and non-design points includes: Based on the determined engine design parameters, calculate the reference operating state parameters and correction coefficients of temperature, pressure, and flow rate of the high and low pressure compressors and turbines at the design point; under given non-design point altitude, Mach number, and flow rate parameters, perform intake duct performance calculation and engine state iterative calculation, and output the performance parameters of each component.

7. The method according to claim 1, characterized in that, The construction of the aircraft and engine indicator system database includes: Create a core data table containing fields for indicator name, parent level, self level, and top-level task name to define a three-layer structure of task layer, capability layer, and indicator layer; populate the database with preset seed data, and interactively supplement and verify the completeness of missing indicator data.

8. The method according to claim 1, characterized in that, In S4, the comprehensive performance evaluation includes: A hierarchical model containing a target layer, a criterion layer, and a scheme layer is constructed; a fuzzy judgment matrix is ​​constructed using triangular fuzzy numbers, and the fuzzy weights of each criterion are calculated; a comprehensive evaluation result is obtained through fuzzy weighted summation, and after defuzzification and consistency verification, a comprehensive performance score is output.

9. A computer terminal device, characterized by include: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors perform the steps of the method as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-8.

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