A multi-subsystem integrated system architecture design optimization method and a multi-subsystem integrated system

Abstract

The embodiment of the application discloses a kind of multi-subsystem comprehensive system architecture design optimization method and the comprehensive system of multi-subsystem, and multi-subsystem includes the flight control subsystem of aircraft, hydraulic subsystem and power subsystem, design method includes: determining the multiple selection of actuator execution mechanism used by flight control subsystem, determine multiple types of form selected by hydraulic subsystem, determine multiple power supply forms of power subsystem;Based on the requirement of operating cost and maintenance cost in series aircraft design, the optimization target that makes operating cost and maintenance cost meet the income demand is determined;For each optimization target determined, its objective function is constructed, and each objective function is solved using multiple sets of design variables to obtain the corresponding solution of each objective function under multiple sets of design variables;The corresponding solution obtained by multiple optimization targets under multiple sets of design variables is comprehensively processed to obtain the feasible solution of the system architecture selection of multi-subsystem, and the final selected system architecture is determined.

Description

Technical Field

[0001] This invention relates to, but is not limited to, the field of aircraft management system technology, specifically to a system architecture design optimization method for multi-subsystem integration, and a multi-subsystem integrated system. Background Technology

[0002] Series design of aircraft avionics systems is a method of simultaneously designing multiple products within a certain market scope. The advantage of this design approach is that if some components, parts, or processes are shared among different products, acquisition costs can be reduced, as well as development and production costs.

[0003] Aircraft management systems (AMS) are complex systems engineering projects integrating aviation electromechanical and flight control designs. They encompass multiple subsystems and devices, including flight control, hydraulics, electrical systems, and environmental control. The system architecture design of an AMS involves defining a clear conceptual model of the system architecture and behavior for this integrated system of multiple subsystems. How to conduct comprehensive optimization design of the architecture of multiple subsystems from the top-level system architecture stage in the early conceptual model design phase is crucial to the functionality, performance, and future mission requirements of the next-generation AMS.

[0004] Current system architecture design methods for multi-subsystem integration often rely on experience or existing mature system architectures, without quantitatively weighing system architecture trade-offs. Sometimes, they only consider a small subset of all possible architectures and offer trade-offs based on semi-quantitative metrics (primarily experience-based). However, these traditional system architecture design methods can be influenced by expert bias, subjectivity, conservatism, or overconfidence. Summary of the Invention

[0005] The purpose of this invention is to address the aforementioned technical problems by providing a system architecture design optimization method for multi-subsystem integration, as well as a multi-subsystem integrated system, to solve the problem that current multi-subsystem integrated system architecture design methods may be affected by expert bias, subjectivity, conservatism, or overconfidence.

[0006] The technical solution of the present invention: In a first aspect, embodiments of the present invention provide a system architecture design optimization method for multi-subsystem integration, wherein the multi-subsystem includes at least an aircraft flight control subsystem, a hydraulic subsystem, and an electrical subsystem, and the system architecture design optimization method includes:

[0007] Step 1: Determine the design variables, including: determining the various types of actuators used in the flight control subsystem, determining the various types of hydraulic subsystems, and determining the various power supply types for the electrical subsystem;

[0008] Step 2, determining optimization targets, including: for the same type of series aircraft, including the following three types: regular type, short-range type and long-range type; based on the requirements of operating cost and maintenance cost in the design of series aircraft, at least one optimization target is determined to make the operating cost and maintenance cost meet the income demand;

[0009] Step 3, optimizing each optimization target determined in step 2, including: constructing the objective function of each optimization target, using multiple groups of design variables to solve each objective function, and obtaining the corresponding solution of each objective function under multiple groups of design variables;

[0010] Step 4, comprehensively processing the corresponding solutions of multiple optimization targets under multiple groups of design variables to obtain a feasible solution of the system architecture selection of multiple subsystems, and determining the final selected system architecture.

[0011] Optionally, in the multi-subsystem comprehensive system architecture design optimization method described above, the step 1 includes:

[0012] Step 11, determining multiple selection forms of actuator execution mechanisms used by the flight control subsystem, including: selection form 1, using all electric actuation execution mechanisms; selection form 2, using all hydraulic actuation execution mechanisms; selection form 3, using part of electric actuation execution mechanisms and part of hydraulic actuation execution mechanisms;

[0013] Step 12, determining multiple selection forms of the hydraulic subsystem according to multiple hydraulic sources of the hydraulic subsystem and the types of pumps used;

[0014] Step 13, determining multiple power supply forms of the electric power subsystem, including: constant speed and constant frequency alternating current power supply, variable frequency alternating current power supply, and 270V high-voltage direct current power supply system.

[0015] Optionally, in the multi-subsystem comprehensive system architecture design optimization method described above, the step 12 includes:

[0016] According to the three hydraulic sources used by the hydraulic subsystem, combined with three types of pumps, by configuring independent or combined pumps for each hydraulic source, multiple selection forms of the hydraulic subsystem in step 12 are formed, wherein the three types of pumps include engine driven pump EDP, electric pump EMP and ram air turbine RAT; the three types of selection forms of the hydraulic subsystem determined in step 12 include:

[0017] Selection form 1: hydraulic source A: 1EDP; hydraulic source B: 1EMP+1RAT; hydraulic source C: 1EDP+1EMP;

[0018] Option form 2: hydraulic source A: 2EDP+1EMP+1RAT; hydraulic source B: 1EDP+1EMP; hydraulic source C: 1EDP+1EMP;

[0019] Option form 3: hydraulic source A: 1EDP+1EMP; hydraulic source B: 1EMP; hydraulic source C: 1EDP+1EMP.

[0020] Optionally, in the system architecture design optimization method of the multi-subsystem comprehensive system as described above, the step 2 comprises:

[0021] Step 21, based on the operating cost requirements of the airline, calculating the total fuel consumption based on the load-range-frequency statistical diagram, and taking the total fuel consumption as the first optimization target;

[0022] Step 22, based on the maintenance cost requirements of the aircraft, selecting the system basic reliability as the second optimization target.

[0023] Optionally, in the system architecture design optimization method of the multi-subsystem comprehensive system as described above, the optimization process for the optimization target 1 in the step 3 comprises:

[0024] Step A1, constructing a target function 1 for the optimization target 1, comprising: constructing a total fuel consumption target function, taking the total fuel consumption target function of the load-range-frequency statistical diagram as the target function 1;

[0025] Step A2, calculating the capability curves and the total fuel consumption of the three types of aircraft without considering the mass changes of the flight control subsystem, the hydraulic subsystem and the power subsystem;

[0026] Step A3, calculating the total fuel consumption of the three types of aircraft considering the mass changes of the flight control subsystem, the hydraulic subsystem and the power subsystem.

[0027] Optionally, in the system architecture design optimization method of the multi-subsystem comprehensive system as described above, the step A1 comprises:

[0028] Step A1-1, obtaining a load-range-frequency statistical diagram, i.e. a PL-R diagram;

[0029] Step A1-2, taking the total fuel consumption target function of the three types of aircraft covering the PL-R diagram as the target function 1 of the optimization target 1, expressed as:

[0030]

[0031] Wherein, M represents the total number of flights in the PL-R graph, M1 represents the number of flights to be flown by the long-range aircraft in the PL-R graph, M2 represents the number of flights to be flown by the regular aircraft in the PL-R graph, and M3 represents the number of flights to be flown by the short-range aircraft in the PL-R graph. fuel(i) represents the fuel consumption of each type of aircraft flying the i-th flight.

[0032] Optionally, in the system architecture design optimization method of multi-subsystem integration as described above, the calculation method in step A2 is:

[0033] Based on the Breguet range calculation formula, and the balance relationship between the lift and gravity, thrust and resistance of the aircraft, a discrete cruise state range calculation formula and a fixed range fuel consumption calculation formula are established, and the capability curves of the three types of aircraft are determined, and the total fuel consumption of the three types of aircraft is calculated.

[0034] Optionally, in the system architecture design optimization method of multi-subsystem integration as described above, step A2 includes:

[0035] Step A2-1, calculate the capability curve of the long-range aircraft, the calculation method is: according to the maximum value of the longitudinal coordinate and the maximum value of the horizontal coordinate of the PL-R graph, select the maximum range value MaxRange and the maximum payload value MaxPayload of the long-range aircraft, calculate the capability curve of the long-range aircraft through the range calculation formula and the fixed range fuel consumption calculation formula, judge whether the capability curve meets the coverage condition, that is, whether it covers all data points in the PL-R graph, if it is judged that it can be covered, the capability curve is determined as the capability curve of the long-range aircraft; Otherwise, adjust the capability curve by increasing the maximum payload value MaxPlayload until the calculated capability curve of the long-range aircraft meets the coverage condition;

[0036] Step A2-2, calculate the capability curves of the regular and short-range aircrafts, and calculate the total fuel consumption of the three types of aircraft, including: initializing the maximum range value MaxRange and the maximum payload value MaxPayload of the regular and short-range aircrafts, calculating the capability curves of the regular and short-range aircrafts through the range calculation formula and the fixed range fuel consumption calculation formula respectively; According to the capability curves of the three types of aircraft, determine the flight tasks of the three types of aircraft in the PL-R graph, and calculate the total fuel consumption according to the objective function 1 in step 3;

[0037] Step A2-3, using an optimization algorithm, optimizing the total fuel consumption as the optimization target, and taking the maximum range value MaxRange and the maximum payload value MaxPayload of the conventional and short-haul aircraft as variables until the total fuel consumption meets the optimization stopping condition; wherein the optimization stopping condition has two methods: fixed optimization iteration times, and the difference between the total fuel consumptions obtained by twice iteration calculation is less than the set threshold.

[0038] Optionally, in the multi-subsystem integrated system architecture design optimization method as described above, the step A3 includes:

[0039] Step A3-1, calculating the fuel mass carried by the three types of aircraft, including: according to the maximum range value MaxRange and the maximum payload value MaxPayload of the three types of aircraft determined in steps A2-1 and A2-2, calculating the fuel mass carried by the three types of aircraft as the initial value of the fuel mass carried by the three types of aircraft through the fixed range fuel calculation formula;

[0040] Step A3-2, performing convergence calculation on the fuel mass carried by the three types of aircraft, including: initializing the values of the design variables of the flight control subsystem, the hydraulic subsystem and the electric power subsystem, combining the initial value of the fuel mass carried by the three types of aircraft calculated, calculating the maximum take-off weight of the three types of aircraft; according to the maximum take-off weight of the three types of aircraft and the calculated capability curve of the three types of aircraft, updating the fuel mass carried by the three types of aircraft, and recalculating the maximum take-off weight of the three types of aircraft according to the updated fuel mass until the fuel mass meets the convergence condition; wherein the convergence condition judgment method: the difference between the fuel masses carried by the three types of aircraft obtained by twice iteration calculation is less than the set threshold;

[0041] Step A3-3, calculating the total fuel consumption of the three types of aircraft considering the mass changes of the flight control subsystem, the hydraulic subsystem and the electric power subsystem according to the fuel mass carried by the three types of aircraft obtained by the convergence calculation;

[0042] Step A3-4, obtaining the total fuel consumption under different design variable values by repeatedly executing steps A3-2 and A3-3 and reinitializing the values of the design variables of the flight control subsystem, the hydraulic subsystem and the electric power subsystem in step A3-2.

[0043] Optionally, in the multi-subsystem integrated system architecture design optimization method as described above, the optimization processing for the optimization target 2 in step 3 includes:

[0044] Step B1, constructing the objective function 2 for the optimization target 2, including: constructing the system basic reliability objective function, that is, the overall system reliability function formed by connecting the flight control subsystem, the hydraulic subsystem and the electric power subsystem of the three types of aircraft in series, as the system basic reliability objective function;

[0045] Step B2, calculating the system basic reliability, including: for the flight control subsystem, the hydraulic subsystem and the electric power subsystem of the three types of aircraft, substituting the corresponding device failure rate data under multiple groups of design variables into the objective function 2 to calculate the system basic reliability corresponding to each group of design variables.

[0046] Optionally, in the multi-subsystem comprehensive system architecture design optimization method described above, the step 4 includes:

[0047] Step 41, forming a feasible solution set of the system architecture selection of the multi-subsystem through genetic algorithm optimization;

[0048] Step 42, generating a Pareto front according to the feasible solution set of the system architecture selection of the multi-subsystem obtained in step 42, and determining the final selected system architecture.

[0049] In a second aspect, the embodiments of the present application also provide a comprehensive system of multi-subsystems, wherein the multi-subsystems of the comprehensive system at least include the flight control subsystem, the hydraulic subsystem and the electric power subsystem of an aircraft; and the selected forms of the architectures of the subsystems in the comprehensive system are obtained by using the multi-subsystem comprehensive system architecture design optimization method described in any one of the above.

[0050] The embodiments of the present application provide a multi-subsystem comprehensive system architecture design optimization method and a comprehensive system of multi-subsystems, the system architecture design optimization method considers multiple subsystems in the system; in the architecture selection in the early conceptual design stage, the function of each subsystem is decomposed, the key design elements are analyzed, the perfect architecture optimization space is constructed, the complex coupling relationship and the associated influence among multiple disciplines are considered, the inherent nature index and the corresponding optimization strategy of each discipline are determined, in the overall design process, the conflict between the local optimal and the global optimization index is solved based on the optimization target, the crosslinking and the selection among the subsystems are coordinated, the requirements for the overall machine index are met by using the least iteration and the best index performance verification method, and the design, improvement and optimization direction of each subsystem are determined.

[0051] The multi-subsystem integrated system architecture design optimization method provided by the embodiment of the application is suitable for integrated architecture design and evaluation of a plurality of key airborne subsystems of a series of aircraft, ensures that in the early conceptual design stage, overall configuration of a plurality of subsystems can be fully considered instead of configuration of a single component or function and coupling relationship between subsystems; on the premise of clear design variables and optimization objectives, in the face of a large number of architecture configuration combination schemes of a flight control subsystem, a power subsystem and a hydraulic subsystem, a global optimal solution is found through an optimization algorithm, and guiding opinions are provided for development of the subsystems in the future to improve overall performance indicators, and the optimization architecture system based on MDO can support application of similar application scenarios involving multidisciplinary optimization design. BRIEF DESCRIPTION OF DRAWINGS

[0052] The accompanying drawings are included to provide a further understanding of the technical scheme of the application, and constitute a part of the specification, and are used together with the embodiments of the application to explain the technical scheme of the application, and do not constitute a limitation on the technical scheme of the application.

[0053] Figure 1 The flowchart of the multi-subsystem integrated system architecture design optimization method provided by the embodiment of the application is shown in FIG. 1.

[0054] Figure 2 The flowchart of another multi-subsystem integrated system architecture design optimization method provided by the embodiment of the application is shown in FIG. 2.

[0055] Figure 3 The schematic diagram of the Pareto front result in the embodiment 1 of the application is shown in FIG. 3.

[0056] Figure 4 The schematic diagram of the Pareto front result in the embodiment 2 of the application is shown in FIG. 4. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical scheme and advantages of the application more clear and understandable, the embodiments of the application will be described in detail below with reference to the drawings. It should be noted that the embodiments in the application and the features in the embodiments can be combined with each other in any manner without conflict.

[0058] As described above in the background, the necessity of series design of aircraft airborne systems and the problems in the current multi-subsystem integrated system architecture design method, that is, the current method is based on experience or mature system architecture, and there is no quantitative trade-off for the system architecture, or sometimes only a small part of all possible architectures is considered, and some trade-offs are given according to semi-quantitative metrics (mainly based on experience); the above traditional system architecture design method may be affected by expert bias, subjectivity, conservatism or overconfidence.

[0059] In addition, objectively speaking, due to the expansion of the design space, the overall configuration of multiple subsystems needs to be considered instead of the configuration of a single component or function. At this time, the number of architecture configuration combination schemes of the flight control subsystem, the power subsystem, the hydraulic subsystem and the environmental control subsystem is very large, and a more detailed and perfect implementation needs to be used to comprehensively analyze the system architecture.

[0060] In view of the above problems and the design requirements of multiple systems, the embodiment of the application provides a multi-subsystem comprehensive system architecture design optimization method and a comprehensive system of multiple subsystems, and takes the system architecture design of key subsystems of a series aircraft, i.e., a flight control subsystem, a hydraulic subsystem and a power subsystem, as the object, and develops the system architecture optimization and product selection of the aircraft management system based on the method of MDO.

[0061] The following specific embodiments provided by the application can be combined with each other, and the same or similar concepts or processes can not be described in some embodiments.

[0062] Figure 1 A flowchart of a multi-subsystem comprehensive system architecture design optimization method provided by the embodiment of the application. The multiple subsystems in the embodiment of the application at least include a flight control subsystem, a hydraulic subsystem and a power subsystem of an aircraft; as shown in the figure, the multi-subsystem comprehensive system architecture design optimization method provided by the embodiment of the application includes the following steps: Figure 1

[0063] Step 1, determining design variables, including: determining multiple selection types of actuator execution mechanisms used by the flight control subsystem, determining multiple types of the hydraulic subsystem, and determining multiple power supply forms of the power subsystem.

[0064] In the design variables of the embodiment of the application, for the flight control subsystem, the hydraulic subsystem and the power subsystem of the aircraft, the flight control subsystem can select different types of actuator execution mechanisms; the hydraulic subsystem generally uses three hydraulic sources, and three independent hydraulic sources are formed by combining the independent or combined selection and use of three types of pumps in each hydraulic source; the power subsystem mainly considers multiple types of power supply forms.

[0065] Step 1, determining design variables, including: determining multiple selection types of actuator execution mechanisms used by the flight control subsystem, determining multiple types of the hydraulic subsystem, and determining multiple power supply forms of the power subsystem;

[0066] Step 2, determining optimization objectives, including: for the same type of series aircraft, including the following three types: a conventional type, a short-range type and a long-range type; based on the requirements of the operating cost and the maintenance cost in the design of the series aircraft, at least one optimization objective is determined to make the operating cost and the maintenance cost meet the income demand; ​

[0067] Step 3, optimizing each optimization target determined in step 2, including: constructing a target function for each optimization target, solving each target function by using multiple sets of design variables, and obtaining corresponding solutions of each target function under multiple sets of design variables;

[0068] Step 4, comprehensively processing the corresponding solutions of multiple optimization targets under multiple sets of design variables to obtain a feasible solution of the system architecture selection of multiple subsystems, and determining the final selected system architecture.

[0069] In an implementation manner of the embodiment of the present application, the implementation process of step 1 can include:

[0070] Step 11, determining multiple selection forms of the actuator execution mechanism used by the flight control subsystem, including: selection form 1, using all electric actuation execution mechanisms; selection form 2, using all hydraulic actuation execution mechanisms; selection form 3, using part of electric actuation execution mechanisms and part of hydraulic actuation execution mechanisms;

[0071] Step 12, determining multiple selection forms of the hydraulic subsystem according to multiple hydraulic sources of the hydraulic subsystem and the types of pumps used;

[0072] Step 13, determining multiple power supply forms of the electric power subsystem, including: constant-speed constant-frequency alternating current power supply, variable-frequency alternating current power supply, and 270V high-voltage direct current power supply system.

[0073] In an implementation manner of the embodiment of the present application, the implementation process of step 2 can include:

[0074] Step 21, calculating total fuel consumption based on the load-range-frequency statistical diagram and taking the total fuel consumption as the first optimization target based on the operation cost requirement of the airline;

[0075] Step 22, selecting the system basic reliability as the second optimization target based on the maintenance cost requirement of the aircraft.

[0076] For different optimization targets selected in step 2, the optimization can be performed by constructing the target function form of each optimization target, and the optimization processing modes of different optimization targets are provided in the following specific embodiments.

[0077] Based on the multi-subsystem comprehensive system architecture design optimization method provided in the above embodiments of the present application, the embodiment of the present application further provides a comprehensive system of multiple subsystems, wherein the multiple subsystems of the comprehensive system at least include the flight control subsystem, the hydraulic subsystem and the electric power subsystem of the aircraft; and the selection form of the architecture of each subsystem in the comprehensive system is obtained by using the multi-subsystem comprehensive system architecture design optimization method provided in any of the above embodiments.

[0078] This invention provides a system architecture design optimization method for multi-subsystem integration, as well as a comprehensive system of multi-subsystems. This system architecture design optimization method considers multiple subsystems within the system. Using this design method, in the early conceptual design phase, the functions of each subsystem are decomposed, key design elements are analyzed, and a comprehensive architecture optimization space is constructed. Simultaneously, the complex coupling relationships and interrelationships between multiple disciplines are considered, clarifying the inherent performance indicators and corresponding optimization strategies within each discipline. During the overall design process, based on the optimization objectives, the conflict between local optima and global optimization indicators is resolved, and the cross-linking and selection between subsystems are coordinated. The system meets the overall performance requirements with minimal iterations and optimal performance verification methods, determining the design, improvement, and optimization directions for each subsystem.

[0079] The system architecture design optimization method for multi-subsystem integration provided in this invention is applicable to the integrated architecture design and evaluation of multiple key airborne subsystems in a series of aircraft. It ensures that in the early conceptual design stage, the overall configuration of multiple subsystems can be fully considered, rather than the configuration of individual components or functions, as well as the coupling relationships between subsystems. Under the premise of clearly defined design variables and optimization objectives, facing a large number of architectural configuration combinations for flight control subsystems, electrical subsystems, and hydraulic subsystems, the optimization algorithm finds the global optimal solution and provides guidance for the development of subsystems in the future to improve overall performance indicators. At the same time, the optimized architecture system based on MDO can support similar application scenarios involving multidisciplinary optimization design.

[0080] The following specific embodiments illustrate the system architecture design optimization method for multi-subsystem integration provided by the present invention, as well as the implementation method of the integrated multi-subsystem system.

[0081] Example

[0082] like Figure 2 The diagram shows a flowchart of another system architecture design optimization method for multi-subsystem integration provided by an embodiment of the present invention. This embodiment provides a system architecture design optimization method for multi-subsystem integration in an aircraft management system (flight control subsystem, hydraulic subsystem, and electrical subsystem). The design process includes the following steps:

[0083] Step 1: Determine the design variables;

[0084] In this step, for the flight control subsystem, hydraulic subsystem and power subsystem of the aircraft, the flight control subsystem can select different types of actuator execution mechanisms; the hydraulic subsystem generally uses three hydraulic sources, combined with the independent or combined selection of three types of pumps in each hydraulic source, to form three independent hydraulic sources; the power subsystem mainly considers various types of power supply forms.

[0085] The implementation process of this step 1 can include:

[0086] For the flight control subsystem of the aircraft, different types of actuator execution mechanisms can be selected, so that the multiple selection forms of the actuator execution mechanisms used by the flight control subsystem can be determined first, including: selection form 1, all using electric actuation execution mechanisms; selection form 2, all using hydraulic actuation execution mechanisms; selection form 3, part using electric actuation execution mechanisms and part using hydraulic actuation execution mechanisms. The design variable used to represent the selection form of the flight control subsystem in this embodiment is represented by the variable “FCS Power Supply”.

[0087] For the hydraulic subsystem of the aircraft, three hydraulic sources are generally used, combined with three types of pumps (including engine driven pump EDP, electric pump EMP, ram air turbine RAT), by configuring independent or combined pumps for each hydraulic source, to form multiple selection forms of the hydraulic subsystem. The selection forms of three typical hydraulic subsystems in this embodiment include:

[0088] Selection form 1: hydraulic source A: 1EDP; hydraulic source B: 1EMP+1RAT; hydraulic source C: 1EDP+1EMP;

[0089] Selection form 2: hydraulic source A: 2EDP+1EMP+1RAT; hydraulic source B: 1EDP+1EMP; hydraulic source C: 1EDP+1EMP;

[0090] Selection form 3: hydraulic source A: 1EDP+1EMP; hydraulic source B: 1EMP; hydraulic source C: 1EDP+1EMP;

[0091] The design variable used to represent the selection form of the hydraulic subsystem in this embodiment is represented by “Hydraulic Power Source”.

[0092] For the power subsystem of the aircraft, the power supply forms mainly considered include: constant speed and constant frequency alternating current power supply, variable frequency alternating current power supply, and 270V high voltage direct current power supply system. The design variable used to represent the power supply form of the power subsystem in this embodiment is represented by “Power System Architecture”.

[0093] Step 2, determining optimization target, including: for the same type of series aircraft, including the following three types: regular type, short-range type and long-range type. Based on the requirements of operating cost and maintenance cost in the design of series aircraft, at least one optimization target is determined to make the operating cost and maintenance cost meet the income demand.

[0094] Considering that the better the product performance is for the design, the lower the operating cost and maintenance cost are, and the greater the income that can be brought to the airline is. Therefore, step 2 in the embodiment includes the following optimization target setting method:

[0095] On the one hand, the operating cost of the airline is mainly fuel consumption, which directly depends on the specific fuel consumption (SFC), the weight of the aircraft and the flight route. Therefore, the total fuel consumption covering the load-range-frequency statistical chart is selected as the first optimization target.

[0096] On the other hand, the maintenance cost of the aircraft mainly depends on the reliability of different components and the number of components, which is directly related to the architecture. The basic reliability of the product is related to the performance and service life of the product, so the system basic reliability is selected as the second optimization target.

[0097] For the optimization target 1 determined in step 2, the optimization target 1 is optimized by the following steps 3-5, specifically including:

[0098] Step 3, constructing target function 1 for optimization target 1, including: constructing total fuel consumption target function, taking the total fuel consumption target function of the load-range-frequency statistical chart (PL-R chart) as the target function 1. The implementation process of this step 3 can include:

[0099] Step 3.1, according to the literature, obtaining the load-range-frequency statistical chart, i.e. PL-R chart;

[0100] Step 3.2, taking the total fuel consumption of the three types of aircraft covering the PL-R chart as the target function 1, expressed as:

[0101]

[0102] Wherein, M represents the total number of flights in the PL-R chart, M1 represents the number of flights to be flown by the long-range aircraft in the PL-R chart, M2 represents the number of flights to be flown by the regular aircraft in the PL-R chart, and M3 represents the number of flights to be flown by the short-range aircraft in the PL-R chart; Flight fuel(i) represents the fuel consumption of each type of aircraft flying the i th flight.

[0103] Step 4, outer layer optimization: calculate the capability curves and total fuel consumption of the three types of aircraft without considering the mass changes of the flight control subsystem, hydraulic subsystem and power subsystem in the aircraft management system.

[0104] The calculation method in this step 4 is: based on the Breguet range calculation formula and the balance relationship between the lift and gravity of the aircraft and the thrust and resistance, a discrete cruise state range calculation formula and a fixed range fuel consumption calculation formula are established, and then the capability curves of the three types of aircraft are determined, and the total fuel consumption of the three types of aircraft is calculated; the three types of aircraft are calculated by the following methods respectively:

[0105] Step 4.1, calculate the capability curve of the long-range type aircraft, the calculation method is: according to the maximum value of the longitudinal coordinate and the maximum value of the horizontal coordinate of the PL-R graph, select the maximum range value MaxRange and the maximum load value MaxPayload of the long-range type aircraft, calculate the capability curve of the long-range type aircraft through the range calculation formula and the fixed range fuel consumption calculation formula, judge whether the capability curve meets the coverage condition, that is, whether it covers all data points in the PL-R graph, when it is judged to be covered, the capability curve is determined as the capability curve of the long-range type aircraft; otherwise, adjust the capability curve by increasing the maximum load value MaxPlayload until the calculated capability curve of the long-range type aircraft meets the coverage condition;

[0106] Step 42, calculate the capability curves of the regular type and short-range type aircrafts, and calculate the total fuel consumption of the three types of aircraft, including: initializing the maximum range value MaxRange and the maximum load value MaxPayload of the regular type and short-range type aircrafts, calculating the capability curves of the regular type and short-range type aircrafts through the range calculation formula and the fixed range fuel consumption calculation formula respectively; according to the capability curves of the three types of aircraft, determine the flight tasks of the three types of aircraft in the PL-R graph, and calculate the total fuel consumption according to the objective function 1 in step 3;

[0107] Step 43, use an optimization algorithm to optimize the total fuel consumption as the optimization target and the maximum range value MaxRange and the maximum load value MaxPayload of the regular type and short-range type aircrafts as variables until the total fuel consumption meets the optimization stopping condition; wherein there are two methods to judge the optimization stopping condition: fixed optimization iteration times, and the difference between the total fuel consumption calculated by two iterations is less than a set threshold.

[0108] Step 5, calculate the total fuel consumption of the three types of aircraft considering the mass changes of the flight control subsystem, hydraulic subsystem and power subsystem in the aircraft management system. The specific calculation process of this step 5 can include:

[0109] Step 51, calculating the fuel mass carried by the three types of aircraft, including: according to the maximum range value MaxRange and the maximum payload value MaxPayload of the three types of aircraft determined in steps 41 and 42, calculating the fuel mass carried by the three types of aircraft as the initial value of the fuel mass carried by the three types of aircraft through the calculation formula of the fuel required for a fixed range;

[0110] Step 52, performing convergence calculation on the fuel mass carried by the three types of aircraft, including: initializing the values of the design variables of the flight control subsystem, the hydraulic subsystem and the power subsystem, combining the initial value of the fuel mass carried by the three types of aircraft calculated, calculating the maximum take-off weight of the three types of aircraft; according to the maximum take-off weight of the three types of aircraft and the calculated capability curve of the three types of aircraft, updating the fuel mass carried by the three types of aircraft, and recalculating the maximum take-off weight of the three types of aircraft according to the updated fuel mass until the fuel mass meets the convergence condition; wherein the convergence condition judgment method: the difference between the fuel masses carried by the three types of aircraft calculated by two iterations is less than a set threshold.

[0111] Step 53, calculating the total fuel consumption of the three types of aircraft considering the mass changes of the flight control subsystem, the hydraulic subsystem and the power subsystem in the aircraft management system according to the fuel mass carried by the three types of aircraft obtained by the convergence calculation.

[0112] For the optimization target 2 determined in step 2, the optimization target 2 is optimized through steps 6-7, specifically including:

[0113] Step 6, constructing the objective function 2 for the optimization target 2, including: constructing the system basic reliability objective function, that is, the overall system reliability function formed by connecting the flight control subsystem, the hydraulic subsystem and the power subsystem of the three types of aircraft, as the system basic reliability objective function.

[0114] It should be noted that the failure rate is a characteristic parameter of the system basic reliability objective function, and the basic reliability of the objective function 2 is equal to the sum of the failure rates of the devices in the flight control subsystem, the hydraulic subsystem and the power subsystem of the three types of aircraft.

[0115] Step 7, calculating the system basic reliability, including: for the flight control subsystem, the hydraulic subsystem and the power subsystem of the three types of aircraft, substituting the corresponding device failure rate data under multiple groups of design variables into the objective function 2 to calculate the system basic reliability corresponding to each group of design variables.

[0116] After the optimization of the above optimization target 1 and optimization target 2, the method provided by the embodiment further includes the following step:

[0117] Step 8, forming a feasible solution of the system architecture selection of the multiple subsystems through genetic algorithm optimization.

[0118] The implementation of this step includes: setting the selection, crossover and mutation probabilities, population size and iteration number; generating multiple individuals in the initial population according to multiple sets of design variables, calculating the target function 1 and target function 2 values of each individual in the initial population, and sorting the individuals in the population based on the calculated values (sorting algorithm: non-dominated quick sort, congestion calculation); calling the selection, crossover and mutation functions to form new individuals; calculating the target function 1 and target function 2 values of the new individuals, sorting the current population and the new individuals, and updating the population according to the sorting results; then calling the selection, crossover and mutation functions again to form new individuals until the convergence condition is met, forming a feasible solution set of the system architecture selection of the multiple subsystems; the convergence condition of this step is: the number of iterations.

[0119] Step 9, generating a Pareto frontier from the feasible solution set of the system architecture selection of the multiple subsystems obtained in step 8 to determine the final selected system architecture, including: for the feasible solution set of the target function 1 and the target function 2, determining the Pareto frontier (i.e. the solution that cannot improve the value of one target function without reducing the value of the other target function), the Pareto frontier represents the trade-off between the achievable constraints and optimization objectives, and the specific selection of which solution (which architecture combination form and equipment selection) depends on the specific needs and preferences of the decision maker, such as the decision maker who values the operating cost (fuel consumption) more, may tend to choose the solution on the left side of the frontier (the horizontal coordinate represents the fuel consumption); if the decision maker values the maintenance cost (system basic reliability) more, he may choose the solution on the lower side of the frontier (the vertical coordinate represents the basic reliability).

[0120] The following describes the system architecture selection using the multi-subsystem synthesis system architecture design optimization method provided in this embodiment through two implementation examples.

[0121] Implementation Example 1:

[0122] Design variable values:

[0123] Design variable 1, "FCS Power Supply", takes values 0 and 1. "0" represents full selection of hydraulic actuators, and "1" represents full selection of electro-hydraulic actuators.

[0124] Design variable 2, "Hydraulic Power Source", takes values 0, 1 and 2; "0" represents the architecture of 1EDP+1EMP+1RAT+1EDP+1EMP; "1" represents the architecture of 2EDP+1EMP+1RAT+1EDP+1EMP+1RAT+1EDP+1EMP+1EDP+1EMP. "2" represents the architecture of 1EDP+1EMP+1EMP+1EDP+1EMP.

[0125] Design variable 3, "Power System Architecture", takes values of 0, 1 and 2. "0" represents a constant frequency AC power supply system, including main power supply, secondary power supply, auxiliary power supply, emergency power supply, flow generator transformer rectifier, etc. "1" represents an AC frequency AC power supply system, including main power supply, secondary power supply, auxiliary power supply, emergency power supply, etc. "2" is a 270V high-voltage main flow power supply system, including main power supply, auxiliary power supply, secondary power supply, etc.

[0126] The obtained optimization results are as follows:

[0127] Firstly, there are repeated solutions in the 100 solutions obtained by optimization to the last generation, for example, the 2nd and 3rd solutions are the same, and the 1st and 4th solutions are also the same. After merging the same solutions, it is found that there are actually only 20 unique solutions that constitute the Pareto front. As shown in FIG. 1, it is a schematic diagram of the Pareto front result in the embodiment example 1 of the present application. Figure 3

[0128] Next, the 20 unique solutions are marked in the Pareto front diagram. For example, for the 1st solution in the diagram, although it performs well in fuel consumption (objective function 1), it is relatively high in reliability (objective function 2).

[0129] Since all the solutions on the Pareto front are optimal solutions under certain trade-offs, the choice of which solution depends on the specific needs and preferences of the decision maker. In practical applications, it is often necessary to find a balance between multiple objectives. Through comprehensive analysis, it is found that solutions 8 to 13 achieve a better balance between fuel consumption and reliability, and therefore can be used as alternative solutions. For example, solution 8 can significantly improve reliability by slightly increasing fuel consumption compared to solution 7; similarly, solution 13 can significantly reduce fuel consumption at the expense of a small amount of reliability compared to solution 14. Therefore, from the perspective of compromise, solutions 8 to 13 are better choices. Among them, for example, solution 8 corresponds to the architecture selection: long-range aircraft: fly-by-wire subsystem selects electric actuator; hydraulic subsystem selects 1EDP+1EMP+1RAT+1EDP+1EMP; power subsystem selects AC frequency AC power supply system; conventional aircraft: fly-by-wire subsystem selects hydraulic actuator; hydraulic subsystem selects 1EDP+1EMP+1EMP+1EDP+1EMP; power subsystem selects 270V high-voltage main flow power supply system; short-range aircraft: fly-by-wire subsystem selects electric actuator; hydraulic subsystem selects 1EDP+1EMP+1RAT+1EDP+1EMP; power subsystem selects AC frequency AC power supply system.

[0130] Embodiment example 2:

[0131] Values of design variables: ​

[0132] Design variable 1, "FCS Power Supply" takes values 0, 1, 2, and 3. "0" represents hydraulic braking under centralization. "1" represents electro-hydraulic braking under centralization. "2" represents hydraulic braking under distribution. "3" represents electro-hydraulic braking under distribution.

[0133] Design variable 2, "Hydraulic Power Source" takes values 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and 11.

[0134] Wherein, "0" represents pressure of 21 MPA, and configuration of: hydraulic source A1EDP, hydraulic source B1EMP+1RAT, hydraulic source C1EDP+1EMP. "1" represents pressure of 21 MPA, and configuration of: hydraulic source A2EDP+1EMP+1RAT, hydraulic source B1EDP+1EMP, hydraulic source C1EDP+1EMP. "2" represents pressure of 21 MPA, and configuration of: hydraulic source A1EDP+1EMP, hydraulic source B1EMP, hydraulic source C1EDP+1EMP. "3" represents pressure of 21 MPA, and configuration of: hydraulic source A2EDP+1EMP, hydraulic source B2EMP+1RAT, hydraulic source C1EDP+1EMP. "4" represents pressure of 21 MPA, and configuration of: hydraulic source A1EDP+1EMP, hydraulic source B2EMP+1RAT, hydraulic source C1EDP+1EMP. "5" represents pressure of 21 MPA, and configuration of: hydraulic source A2EDP+1EMP, hydraulic source B2EDP+1EMP. "6" represents pressure of 35 MPA, and configuration of: hydraulic source A1EDP, hydraulic source B1EMP+1RAT, hydraulic source C1EDP+1EMP. "7" represents pressure of 35 MPA, and configuration of: hydraulic source A2EDP+1EMP+1RAT, hydraulic source B1EDP+1EMP, hydraulic source C1EDP+1EMP. "8" represents pressure of 351 MPA, and configuration of: hydraulic source A1EDP+1EMP, hydraulic source B1EMP, hydraulic source C1EDP+1EMP. "9" represents pressure of 35 MPA, and configuration of: hydraulic source A2EDP+1EMP, hydraulic source B2EMP+1RAT, hydraulic source C1EDP+1EMP. "10" represents pressure of 35 MPA, and configuration of: hydraulic source A1EDP+1EMP, hydraulic source B2EMP+1RAT, hydraulic source C1EDP+1EMP. "11" represents pressure of 351 MPA, and configuration of: hydraulic source A2EDP+1EMP, hydraulic source B2EDP+1EMP.

[0135] The design variable 3, "Power System Architecture", has values of 0, 1 and 2. "0" represents a constant frequency AC power supply system, including main power supply, secondary power supply, auxiliary power supply, emergency power supply, flow generator transformer rectifier, etc. "1" represents an AC frequency AC power supply system, including main power supply, secondary power supply, auxiliary power supply, emergency power supply, etc. "2" is a 270V high-voltage main flow power supply system, including main power supply, auxiliary power supply, secondary power supply, etc.

[0136] The obtained optimization results are as follows:

[0137] Firstly, there are repeated solutions in the 200 solutions obtained by optimizing to the last generation. After merging the same solutions, it is found that there are actually only 39 unique solutions that constitute the Pareto frontier. As shown in FIG. 1, it is a schematic diagram of the Pareto frontier results in the embodiment 2 of the present application. Figure 4

[0138] Next, the 39 unique solutions are marked in the Pareto frontier diagram. For example, for the No. 1 solution in the diagram, although it performs well in fuel consumption (objective function 1), it is relatively high in reliability (objective function 2).

[0139] Since all the solutions on the Pareto frontier are optimal solutions under certain trade-offs, the choice of which solution depends on the specific needs and preferences of the decision maker. In practical applications, it is often necessary to find a balance between multiple objectives. Through comprehensive analysis, it is found that solutions 11 to 29 have achieved a good balance between fuel consumption and reliability, and therefore can be used as alternative solutions. For example, solution 11 can significantly improve reliability by slightly increasing fuel consumption compared to solution 10; similarly, solution 29 can significantly reduce fuel consumption at the expense of a small amount of reliability compared to solution 30. Therefore, from the perspective of compromise, solutions 11 to 29 are better choices. For example, solution 11 corresponds to the architecture selection: for long-range aircraft: the flight control subsystem selects the electric-hydraulic brake under distribution; the hydraulic subsystem selects a pressure of 35MPA, and the configuration is: hydraulic source A1EDP, hydraulic source B1EMP+1RAT, hydraulic source C1EDP+1EMP; the power subsystem selects an AC frequency AC power supply system. For conventional aircraft: the flight control subsystem selects the hydraulic brake under distribution; the hydraulic subsystem selects a pressure of 35MPA, and the configuration is: hydraulic source A1EDP+1EMP, hydraulic source B2EMP+1RAT, hydraulic source C1EDP+1EMP; the power subsystem selects a 270V high-voltage main flow power supply system. For short-range aircraft: the flight control subsystem selects the hydraulic brake under distribution; the hydraulic subsystem selects a pressure of 35MPA, and the configuration is: hydraulic source A1EDP, hydraulic source B1EMP+1RAT, hydraulic source C1EDP+1EMP; the power subsystem selects an AC frequency AC power supply system.

[0140] ​Although the present application has been described with reference to the above embodiments, the contents are only the embodiments for facilitating the understanding of the present application, and are not intended to limit the present application. Any modification and change in the form and details of the embodiments can be made by any person skilled in the art without departing from the spirit and scope of the present application. The patent protection scope of the present application shall be subject to the scope defined by the appended claims.

Claims

1. A system architecture design optimization method for multi-subsystem integration, characterized in that, The multi-subsystem includes at least the aircraft's flight control subsystem, hydraulic subsystem, and electrical subsystem. The system architecture design optimization method includes: Step 1: Determine the design variables, including: determining the various types of actuators used in the flight control subsystem, determining the various types of hydraulic subsystems, and determining the various power supply types for the electrical subsystem; Step 2, determine the optimization objective, including: for a series of aircraft of the same model, including the following three types: conventional, short-range and long-range; based on the requirements for operating and maintenance costs in the design of the series of aircraft, determine at least one optimization objective that makes the operating and maintenance costs meet the revenue requirements; Step 3: Optimize each optimization objective determined in Step 2, including: constructing an objective function for each optimization objective, solving each objective function using multiple sets of design variables, and obtaining the solution corresponding to each objective function under multiple sets of design variables; Step 4: The corresponding solutions obtained from multiple optimization objectives under multiple sets of design variables are comprehensively processed to obtain a feasible solution for the system architecture selection of multiple subsystems, and the final selected system architecture is determined. Step 4 includes: Step 41: Optimize using a genetic algorithm to form a set of feasible solutions for the system architecture selection of the multi-subsystem. Step 42: Generate the Pareto front based on the feasible solution set of the multi-subsystem system architecture selection obtained in Step 41, and determine the final selected system architecture.

2. The system architecture design optimization method for multi-subsystem integration according to claim 1, characterized in that, Step 1 includes: Step 11: Determine the various selection options for the actuators used in the flight control subsystem, including: Option 1, all electric actuators; Option 2, all hydraulic actuators; Option 3, some electric actuators and some hydraulic actuators. Step 12: Based on the multiple hydraulic sources of the hydraulic subsystem and the type of pump used, determine the various selection options for the hydraulic subsystem; Step 13 identifies the various power supply options for the power subsystem, including: constant speed and constant frequency AC power supply, variable frequency AC power supply, and 270V high voltage DC power supply system.

3. The system architecture design optimization method for multi-subsystem integration according to claim 2, characterized in that, Step 12 includes: Based on the three hydraulic sources used by the hydraulic subsystem and the three types of pumps, various selection options for the hydraulic subsystem in step 12 are formed by configuring pumps for each hydraulic source independently or in combination. The three types of pumps include an engine-driven pump (EDP), an electric pump (EMP), and a ram air turbine (RAT). The three selection options for the hydraulic subsystem determined in step 12 include: Selection Option 1: Hydraulic Source A: 1 EDP; Hydraulic Source B: 1 EMP + 1 RAT; Hydraulic Source C: 1 EDP + 1 EMP; Option 2: Hydraulic source A: 2EDP+1EMP+1RAT; Hydraulic source B: 1EDP+1EMP; Hydraulic source C: 1EDP+1EMP; Option 3: Hydraulic source A: 1EDP+1EMP; Hydraulic source B: 1EMP; Hydraulic source C: 1EDP+1EMP.

4. The system architecture design optimization method for multi-subsystem integration according to claim 3, characterized in that, Step 2 includes: Step 21: Based on the airline's operating cost requirements, calculate the total fuel consumption based on the coverage load-range-frequency statistics chart, and use the total fuel consumption as the optimization objective 1; Step 22: Based on the aircraft's maintenance cost requirements, select basic system reliability as optimization objective 2.

5. The system architecture design optimization method for multi-subsystem integration according to claim 4, characterized in that, The optimization process for optimization objective 1 in step 3 includes: Step A1, construct objective function 1 for optimization objective 1, including: constructing total fuel consumption objective function, with the total fuel consumption objective function covering the load-range-frequency statistics chart as objective function 1; Step A2: Without considering the mass changes of the flight control subsystem, hydraulic subsystem, and electrical subsystem, calculate the capability curves and total fuel consumption of the three types of aircraft. Step A3: Calculate the total fuel consumption of the three types of aircraft, taking into account the mass changes of the flight control subsystem, hydraulic subsystem, and electrical subsystem.

6. The system architecture design optimization method for multi-subsystem integration according to claim 5, characterized in that, Step A1 includes: Step A1-1: Obtain the payload-range-frequency statistics chart, i.e., the PL-R chart; Step A1-2, using the total fuel consumption objective function covering the PL-R map for the three types of aircraft as the objective function 1 of the optimization objective 1, is expressed as: ； Where M represents the total number of flights in the PL-R chart, M1 represents the number of flights waiting to fly for long-range aircraft in the PL-R chart, M2 represents the number of flights waiting to fly for conventional aircraft in the PL-R chart, and M3 represents the number of flights waiting to fly for short-range aircraft in the PL-R chart. Flight fuel(i) This represents the fuel consumption for the i-th flight of each type of aircraft.

7. The system architecture design optimization method for multi-subsystem integration according to claim 5, characterized in that, The calculation method in step A2 is as follows: Based on the Breguet range calculation formula and the balance between lift and gravity, thrust and drag of an aircraft, a discrete cruise range calculation formula and a fixed range fuel requirement calculation formula are established. Then, the capability curves of three types of aircraft are determined, and the total fuel consumption of the three types of aircraft is calculated.

8. The system architecture design optimization method for multi-subsystem integration according to claim 7, characterized in that, Step A2 includes: Step A2-1: Calculate the capability curve of the long-range aircraft. The calculation method is as follows: Based on the maximum value of the vertical axis and the maximum value of the horizontal axis of the PL-R chart, select the maximum range value MaxRange and the maximum payload value MaxPayload of the long-range aircraft. Calculate the capability curve of the long-range aircraft using the range calculation formula and the fuel required for a fixed range calculation formula. Determine whether the capability curve meets the coverage condition, i.e., whether it covers all data points in the PL-R chart. If it is determined that it can cover all data points, then the capability curve is determined as the capability curve of the long-range aircraft; otherwise, adjust the capability curve by increasing the maximum payload value MaxPlayload until the calculated capability curve of the long-range aircraft meets the coverage condition. Step A2-2: Calculate the capability curves for conventional and short-range aircraft, and calculate the total fuel consumption for the three types of aircraft. This includes: initializing the maximum range (MaxRange) and maximum payload (MaxPayload) values ​​for conventional and short-range aircraft; calculating the capability curves for conventional and short-range aircraft using the range calculation formula and the fuel required for a fixed range formula; determining the flight missions for the three types of aircraft in the PL-R diagram based on their capability curves; and calculating the total fuel consumption based on objective function 1 in step 3. Step A2-3: An optimization algorithm is used, with total fuel consumption as the optimization objective, and the maximum range value MaxRange and maximum load value MaxPayload of conventional and short-range aircraft as variables, to optimize until the total fuel consumption meets the optimization stopping condition. There are two methods to determine the optimization stopping condition: fix the number of optimization iterations, and the difference between the total fuel consumption calculated in two iterations is less than a set threshold.

9. The system architecture design optimization method for multi-subsystem integration according to claim 5, characterized in that, Step A3 includes: Step A3-1, calculate the fuel mass carried by the three types of aircraft, including: based on the maximum range value MaxRange and maximum load value MaxPayload of the three types of aircraft determined in steps A2-1 and A2-2, calculate the fuel mass carried by the three types of aircraft as the initial value of the fuel mass carried by the three types of aircraft using the calculation formula for the fuel required for the fixed range. Step A3-2 involves performing convergence calculations on the fuel mass carried by the three types of aircraft, including: initializing the design variables of the flight control subsystem, hydraulic subsystem, and electrical subsystem; calculating the maximum takeoff weight of the three types of aircraft based on the calculated initial values ​​of the fuel mass carried by the three types of aircraft; updating the fuel mass carried by the three types of aircraft based on the maximum takeoff weight of the three types of aircraft and the calculated capability curves of the three types of aircraft; and recalculating the maximum takeoff weight of the three types of aircraft based on the updated fuel mass until the fuel mass meets the convergence condition; wherein, the convergence condition is determined by the difference between the fuel mass carried by the three types of aircraft obtained from two iterations being less than a set threshold. Step A3-3: Based on the fuel mass of the three types of aircraft obtained from the convergence calculation, calculate the total fuel consumption of the three types of aircraft under the condition of considering the mass changes of the flight control subsystem, hydraulic subsystem, and electrical subsystem. Step A3-4 involves repeating steps A3-2 and A3-3, and re-initializing the design variables of the flight control subsystem, hydraulic subsystem, and electrical subsystem in step A3-2 to obtain the total fuel consumption under multiple sets of different design variable values.

10. The system architecture design optimization method for multi-subsystem integration according to claim 4, characterized in that, The optimization process for optimization objective 2 in step 3 includes: Step B1, construct objective function 2 for optimization objective 2, including: constructing the basic system reliability objective function, that is, the overall system reliability function formed by connecting the flight control subsystem, hydraulic subsystem and electric subsystem of the three types of aircraft in series, which is used as the basic system reliability objective function; Step B2, calculate the basic reliability of the system, including: for the flight control subsystem, hydraulic subsystem and electrical subsystem of the three types of aircraft, substitute the equipment failure rate data corresponding to multiple sets of design variables into objective function 2 for calculation, and obtain the basic reliability of the system corresponding to each set of design variables.

11. A multi-subsystem integrated system, characterized in that, The integrated system comprises at least the aircraft's flight control subsystem, hydraulic subsystem, and electrical subsystem; the system architecture design optimization method for the integrated system as described in any one of claims 1 to 10 is used to obtain the selected form of the architecture of each subsystem in the integrated system.

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