Multi-subsystem integrated system architecture design optimization method and multi-subsystem integrated system

Abstract

The embodiment of the invention discloses a multi-subsystem integrated system architecture design optimization method and a multi-subsystem integrated system, multiple subsystems comprise a flight control subsystem, a hydraulic subsystem and an electric power subsystem of an airplane, and the design method comprises the following steps: determining various types of actuator actuating mechanisms used by the flight control subsystem, determining a plurality of types and forms selected by the hydraulic subsystem, and determining a plurality of power supply forms of the electric power subsystem; based on the requirements for the operation cost and the maintenance cost in the serialized aircraft design, determining an optimization target enabling the operation cost and the maintenance cost to meet the income demand; constructing a target function for each determined optimization target, and solving each target function by adopting a plurality of groups of design variables to obtain corresponding solutions of each target function under the plurality of groups of design variables; and comprehensively processing the corresponding solutions obtained by the plurality of optimization targets under the plurality of groups of design variables to obtain a feasible solution of the model selection of the system architecture of the plurality of subsystems, and determining the system architecture of the final model selection.

Description

Technical Field

[0001] The present invention relates to, but is not limited to, the technical field of aircraft management systems, and in particular to a system architecture design optimization method for multi-subsystem integration, and a multi-subsystem integrated system. Background Art

[0002] The serial design of aircraft onboard systems is a way of designing multiple products at the same time within a certain market range. The advantage of this design form is that if some components, parts or processes are shared between different products, the acquisition cost can be reduced, and the development and production costs can be reduced.

[0003] The aircraft management system is a complex system engineering with integrated design of aviation electromechanical and flight control, which includes multiple subsystems and equipment such as flight control, hydraulics, electricity, and environmental control. The system architecture design of the aircraft management system means defining a clear system architecture and behavioral conceptual model for the system integrated with multiple subsystems. How to carry out comprehensive optimization design of the architecture of multiple subsystems from the top-level system architecture level in the early conceptual model design stage is crucial to the functions, performance, and later mission requirements of the new generation of aircraft management systems.

[0004] At present, the system architecture design method of multi-subsystem integration is often based on experience or existing mature system architectures, without quantitatively weighing the system architecture, or sometimes only considers a small part of all possible architectures and gives some trade-offs based on semi-quantitative measurements (mainly based on experience). However, the above traditional system architecture design methods may be affected by expert bias, subjectivity, conservatism or overconfidence. Summary of the invention

[0005] Purpose of the present invention: In order to solve the above-mentioned technical problems, the embodiments of the present invention provide a multi-subsystem integrated system architecture design optimization method and a multi-subsystem integrated system to solve the problem that the current multi-subsystem integrated system architecture design method may be affected by expert bias, subjectivity, conservatism or overconfidence.

[0006] Technical solution of the present invention: In a first aspect, an embodiment of the present invention provides a system architecture design optimization method for a multi-subsystem integration, wherein the multi-subsystem includes at least a flight control subsystem, a hydraulic subsystem, and a power subsystem of an aircraft, and the system architecture design optimization method includes:

[0007] Step 1, determine the design variables, including: determine the various types of actuators used in the flight control subsystem, determine the various types of forms selected by the hydraulic subsystem, and determine the various power supply forms of the power subsystem;

[0008] Step 2, determining the optimization target, including: for the same type of serialized aircraft, including the following three types: conventional, short-range and long-range; based on the requirements for operating costs and maintenance costs in the design of serialized aircraft, determining at least one optimization target that makes the operating costs and maintenance costs meet the revenue requirements;

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

[0010] Step 4, comprehensively process the corresponding solutions of multiple optimization objectives under multiple sets of design variables to obtain feasible solutions for the system architecture selection of multiple subsystems and determine the final selected system architecture.

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

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

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

[0014] Step 13, determining multiple power supply forms of 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.

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

[0016] According to the three hydraulic sources used by the hydraulic subsystem, combined with three types of pumps, by configuring each hydraulic source with a pump used independently or in combination, multiple selection forms of the hydraulic subsystem in step 12 are formed, wherein the three types of pumps include an engine driven pump EDP, an electric pump EMP, and a 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] Selection form 2: Hydraulic source A: 2EDP+1EMP+1RAT; Hydraulic source B: 1EDP+1EMP; Hydraulic source C: 1EDP+1EMP;

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

[0020] Optionally, in the above-mentioned multi-subsystem integrated system architecture design optimization method, step 2 includes:

[0021] Step 21, based on the airline's operating cost requirements, the total fuel consumption is calculated based on the coverage load-range-frequency statistical chart, and the total fuel consumption is used as the first optimization target;

[0022] Step 22, based on the aircraft maintenance cost requirement, select system basic reliability as the second optimization objective.

[0023] Optionally, in the above-mentioned multi-subsystem integrated system architecture design optimization method, the optimization process for optimization target 1 in step 3 includes:

[0024] Step A1, constructing objective function 1 for optimization objective 1, including: constructing a total fuel consumption objective function, taking the total fuel consumption objective function covering the load-range-frequency statistical graph as objective function 1;

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

[0026] Step A3, calculating the total fuel consumption of the three types of aircraft by taking into account the mass changes of the flight control subsystem, hydraulic subsystem, and electrical subsystem.

[0027] Optionally, in the above-mentioned multi-subsystem integrated system architecture design optimization method, step A1 includes:

[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 objective function of the three types of aircraft covering the PL-R diagram as the objective function 1 of the optimization objective 1, expressed as:

[0030]

[0031] Among them, M represents the total number of flights in the PL-R diagram, M1 represents the number of flights waiting to be flown by long-range aircraft in the PL-R diagram, M2 represents the number of flights waiting to be flown by conventional aircraft in the PL-R diagram, and M3 represents the number of flights waiting to be flown by short-range aircraft in the PL-R diagram; Flight fuel(i) represents the fuel consumption of each type of aircraft flying the i-th flight.

[0032] Optionally, in the above-mentioned multi-subsystem integrated system architecture design optimization method, the calculation method in step A2 is:

[0033] Based on the Breguet range calculation formula and the balance relationship between the aircraft's lift and gravity, thrust and drag, a discrete cruise range calculation formula and a calculation formula for the fuel required for a fixed range were established, and then the capacity curves of the three types of aircraft were determined, and the total fuel consumption of the three types of aircraft was calculated.

[0034] Optionally, in the above-mentioned multi-subsystem integrated system architecture design optimization method, step A2 includes:

[0035] Step A2-1, calculating the capability curve of the long-range aircraft, the calculation method is as follows: according to the maximum value of the ordinate and the maximum value of the abscissa of the PL-R diagram, selecting the maximum range value MaxRange and the maximum load value MaxPayload of the long-range aircraft, calculating the capability curve of the long-range aircraft by using the range calculation formula and the calculation formula of the required fuel for a fixed range, judging whether the capability curve meets the coverage condition, that is, whether it covers all the data points in the PL-R diagram, if it is judged that it can cover, then the capability curve is determined as the capability curve of the long-range aircraft; otherwise, adjusting the capability curve by increasing the maximum load value MaxPlayload until the calculated capability curve of the long-range aircraft meets the coverage condition;

[0036] Step A2-2, calculating the capacity curves of conventional and short-range aircraft, and calculating 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 conventional and short-range aircraft, respectively calculating the capacity curves of the conventional and short-range aircraft by using the range calculation formula and the calculation formula of the fuel required for the fixed range; respectively determining the flight missions of the three types of aircraft in the PL-R diagram according to the capacity curves of the three types of aircraft, and calculating the total fuel consumption according to the objective function 1 in step 3;

[0037] Step A2-3, using an optimization algorithm, taking total fuel consumption as the optimization target, and taking the maximum range value MaxRange and the maximum load value MaxPayload of conventional and short-range aircraft as variables for optimization, until the total fuel consumption meets the optimization stop condition; wherein, there are two methods for determining the optimization stop condition: fixing the number of optimization iterations, and the difference in total fuel consumption calculated by two iterations is less than a set threshold.

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

[0039] Step A3-1, calculating the fuel mass carried by the three types of aircraft, comprising: according to the maximum range value MaxRange and the maximum load value MaxPayload of the three types of aircraft determined in step A2-1 and step A2-2, by using a calculation formula for the fuel required for the fixed range, 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;

[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, and calculating the maximum take-off weight of the three types of aircraft in combination with 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 according to the maximum take-off weight of the three types of aircraft and the calculated capacity curves of 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 is: the difference between the fuel mass carried by the three types of aircraft obtained by two iterative calculations is less than a set threshold value;

[0041] Step A3-3, based on the fuel masses carried by the three types of aircraft obtained by 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, the hydraulic subsystem, and the electric subsystem;

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

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

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

[0045] Step B2, calculating the basic reliability of the system, includes: for the flight control subsystem, hydraulic subsystem, and power subsystem of the three types of aircraft, substituting the corresponding equipment failure rate data under multiple sets of design variables into objective function 2 for calculation, and obtaining the basic reliability of the system corresponding to each set of design variables.

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

[0047] Step 41, forming a feasible solution set for selecting a system architecture of multiple subsystems through genetic algorithm optimization;

[0048] Step 42, generating a Pareto frontier based on the feasible solution set for the system architecture selection of the multiple subsystems obtained in step 42, and determining the final selected system architecture.

[0049] In a second aspect, an embodiment of the present invention further provides an integrated system of multiple subsystems, wherein the multiple subsystems of the integrated system include at least a flight control subsystem, a hydraulic subsystem and a power subsystem of the aircraft; and a system architecture design optimization method for a multi-subsystem integration as described in any one of the above items is used to obtain the selected form of the architecture of each subsystem in the integrated system.

[0050] Beneficial effects of the present invention: The embodiment of the present invention provides a system architecture design optimization method for a multi-subsystem integration, and a multi-subsystem integrated system, wherein the system architecture design optimization method takes into account multiple subsystems in the system; using the design method provided by the embodiment of the present invention, in the architecture selection in the early conceptual design stage, the function of each subsystem is decomposed, its key design elements are analyzed, and a complete architecture optimization space is constructed, while considering the complex coupling relationship and associated influences among multiple disciplines, clarifying the inherent sexual development indicators and corresponding optimization strategies within each discipline, and in the overall design process, based on the optimization goal, resolving the conflict between local optimal and global optimization indicators, coordinating the cross-linking and selection between the subsystems, and meeting the requirements for the overall machine indicators with the least iterations and the best indicator performance verification method, and determining the design, improvement and optimization direction of each subsystem.

[0051] The multi-subsystem integrated system architecture design optimization method provided by the embodiment of the present invention is suitable for the integrated architecture design and evaluation of multiple key airborne subsystems of serialized aircraft, ensuring that in the early conceptual design stage, the overall configuration of multiple subsystems can be fully considered, rather than the configuration of a single component or function, and the coupling relationship between subsystems; under the premise of clarifying the design variables and optimization goals, in the face of the huge number of architectural configuration combination schemes of the flight control subsystem, the power subsystem, and the hydraulic subsystem, the global optimal solution is found through the optimization algorithm, and guiding opinions are provided for the development of subsystems in the future to achieve the improvement of overall performance indicators. At the same time, the constructed MDO-based optimization architecture system can support the application of similar application scenarios involving multidisciplinary optimization design. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the technical solution of the present invention and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present invention and do not constitute a limitation on the technical solution of the present invention.

[0053] Figure 1 A flowchart of a multi-subsystem integrated system architecture design optimization method provided by an embodiment of the present invention;

[0054] Figure 2 A flowchart of another multi-subsystem integrated system architecture design optimization method provided by an embodiment of the present invention;

[0055] Figure 3 A schematic diagram of the Pareto front result in Example 1 of the present invention;

[0056] Figure 4 It is a schematic diagram of the Pareto front result in implementation example 2 of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clear, the embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other arbitrarily without conflict.

[0058] The above background technology has explained the necessity of serial design of aircraft onboard systems, as well as the problems existing in the current system architecture design method for multi-subsystem integration, namely, the current system architecture design method is based on experience or borrowing from existing mature system architectures, and does not quantitatively weigh the system architecture, or sometimes only considers a small part of all possible architectures, and gives some trade-offs based on semi-quantitative measurements (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, it is necessary to consider the overall configuration of multiple subsystems rather than the configuration of a single component or function. At this time, the number of architectural configuration combinations of the flight control subsystem, power subsystem, hydraulic subsystem, and environmental control is very large, and a more detailed and complete implementation method is needed to conduct a comprehensive analysis of the system architecture.

[0060] In view of the above problems and multi-system design requirements, an embodiment of the present invention provides a multi-subsystem integrated system architecture design optimization method and a multi-subsystem integrated system, taking the system architecture design of the key subsystems of the serialized aircraft: flight control subsystem, hydraulic subsystem and power subsystem as the object, the system architecture optimization and product selection of the aircraft management system are carried out based on the MDO method.

[0061] The present invention provides the following specific embodiments which can be combined with each other. The same or similar concepts or processes may not be described in detail in some embodiments.

[0062] Figure 1 A flowchart of a multi-subsystem integrated system architecture design optimization method provided in an embodiment of the present invention. The multi-subsystem in the embodiment of the present invention at least includes: a flight control subsystem, a hydraulic subsystem, and a power subsystem of an aircraft; Figure 1 As shown, the multi-subsystem integrated system architecture design optimization method provided by the embodiment of the present invention includes the following steps:

[0063] Step 1, determine the design variables, including: determine the various options for the actuators used by the flight control subsystem, determine the various types of forms selected by the hydraulic subsystem, and determine the various power supply forms of the power subsystem.

[0064] Among the design variables of the embodiments of the present invention, for the flight control subsystem, hydraulic subsystem, and power subsystem of the aircraft, the flight control subsystem can select different types of actuators; 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.

[0065] Step 1, determine the design variables, including: determine the various types of actuators used in the flight control subsystem, determine the various types of forms selected by the hydraulic subsystem, and determine the various power supply forms of the power subsystem;

[0066] Step 2, determining the optimization target, including: for the same type of serialized aircraft, including the following three types: conventional, short-range and long-range; based on the requirements for operating costs and maintenance costs in the design of serialized aircraft, determining at least one optimization target that makes the operating costs and maintenance costs meet the revenue requirements;

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

[0068] Step 4, comprehensively process the corresponding solutions of multiple optimization objectives under multiple sets of design variables to obtain feasible solutions for the system architecture selection of multiple subsystems and determine the final selected system architecture.

[0069] In one implementation of the embodiment of the present invention, the implementation process of the above step 1 may include:

[0070] Step 11, determining multiple selection forms of actuators used by the flight control subsystem, including: selection form 1, all using electric actuators; selection form 2, all using hydraulic actuators; selection form 3, partially using electric actuators and partially using hydraulic actuators;

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

[0072] Step 13, determining multiple power supply forms of 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.

[0073] In one implementation of the embodiment of the present invention, the implementation process of the above step 2 may include:

[0074] Step 21, based on the airline's operating cost requirements, the total fuel consumption is calculated based on the coverage load-range-frequency statistical chart, and the total fuel consumption is used as the first optimization target;

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

[0076] For the different optimization targets selected in step 2, each optimization target can be optimized by constructing an objective function for each optimization target. The following specific embodiments provide optimization processing methods for different optimization targets.

[0077] Based on the system architecture design optimization method for multi-subsystem integration provided by the above-mentioned embodiments of the present invention, an embodiment of the present invention also provides a multi-subsystem integrated system, wherein the multi-subsystems of the integrated system at least include a flight control subsystem, a hydraulic subsystem and a power subsystem of the aircraft; the system architecture design optimization method for multi-subsystem integration provided by any of the above-mentioned embodiments is used to obtain the selection form of the architecture of each subsystem in the integrated system.

[0078] The embodiment of the present invention provides a system architecture design optimization method for a multi-subsystem integration, and a multi-subsystem integrated system, wherein the system architecture design optimization method takes into account multiple subsystems in the system; the design method provided by the embodiment of the present invention is used to decompose the functions of each subsystem in the architecture selection in the early conceptual design stage, analyze its key design elements, and build a complete architecture optimization space, while considering the complex coupling relationship and associated influences between multiple disciplines, clarifying the inherent sexual development indicators and corresponding optimization strategies within each discipline, and in the overall design process, based on the optimization goal, resolving the conflict between local optimal and global optimization indicators, coordinating the cross-linking and selection between the subsystems, and meeting the requirements for the overall machine indicators with the least iterations and the best indicator performance verification method, and determining the design, improvement and optimization direction of each subsystem.

[0079] The multi-subsystem integrated system architecture design optimization method provided by the embodiment of the present invention is suitable for the integrated architecture design and evaluation of multiple key airborne subsystems of serialized aircraft, ensuring that in the early conceptual design stage, the overall configuration of multiple subsystems can be fully considered, rather than the configuration of a single component or function, and the coupling relationship between subsystems; under the premise of clarifying the design variables and optimization goals, in the face of the huge number of architectural configuration combination schemes of the flight control subsystem, the power subsystem, and the hydraulic subsystem, the global optimal solution is found through the optimization algorithm, and guiding opinions are provided for the development of subsystems in the future to achieve the improvement of overall performance indicators. At the same time, the constructed MDO-based optimization architecture system can support the application of similar application scenarios involving multidisciplinary optimization design.

[0080] The following is a schematic illustration of a multi-subsystem integrated system architecture design optimization method and a multi-subsystem integrated system implementation method provided by the present invention through some specific embodiments.

[0081] Example

[0082] like Figure 2 As shown, it is a flowchart of another multi-subsystem integrated system architecture design optimization method provided by an embodiment of the present invention; this embodiment provides a multi-subsystem integrated system architecture design optimization method for multiple subsystems (flight control subsystem, hydraulic subsystem, power subsystem) in an aircraft management system, and the design process includes the following steps:

[0083] Step 1, determine the design variables;

[0084] In this step, for the aircraft's flight control subsystem, hydraulic subsystem, and power subsystem, the flight control subsystem can choose different types of actuators; 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 step 1 may include:

[0086] Different types of actuators can be selected for the flight control subsystem of the aircraft. Therefore, the various selection forms of the actuators used in the flight control subsystem can be determined first, including: Selection form 1, all electric actuators are used; Selection form 2, all hydraulic actuators are used; Selection form 3, some electric actuators are used, and some hydraulic actuators are used. In this embodiment, the design variable used to represent the selection form of the flight control subsystem 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), and each hydraulic source is configured with a pump used independently or in combination to form a variety of selection forms of the hydraulic subsystem. The three typical selection forms of the hydraulic subsystem 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] In this embodiment, the design variable used to represent the selection form of the hydraulic subsystem is represented by "Hydraulic PowerSource".

[0092] For the aircraft power subsystem, the power supply forms are mainly considered, including: constant speed and constant frequency AC power supply, variable frequency AC power supply, and 270V high voltage DC power supply system. In this embodiment, the design variable used to represent the power supply form of the power subsystem is represented by "Power System Architecture".

[0093] Step 2, determine the optimization target, including: for the same type of serialized aircraft, including the following three types: conventional, short-range and long-range. Based on the requirements for operating costs and maintenance costs in the design of serialized aircraft, determine at least one optimization target that makes the operating costs and maintenance costs meet the revenue requirements.

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

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

[0096] On the other hand, the maintenance cost of an 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 a product is related to the performance and service life of the product, so the basic reliability of the system is selected as the second optimization goal.

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

[0098] Step 3, constructing objective function 1 for optimization objective 1, including: constructing a total fuel consumption objective function, with the total fuel consumption objective function covering the load-range-frequency statistical diagram (PL-R diagram) as objective function 1. The implementation process of step 3 may include:

[0099] Step 3.1, according to the literature, obtain the load-range-frequency statistical diagram, that is, the PL-R diagram;

[0100] Step 3.2, the total fuel consumption of the three types of aircraft covering the PL-R diagram is taken as objective function 1, which is expressed as:

[0101]

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

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

[0104] The calculation method in step 4 is: based on the range calculation formula Breguet, and the balance relationship between the lift and gravity, thrust and drag of the aircraft, a discrete cruising range calculation formula and a calculation formula for the fuel required for a fixed range are established, and then the capacity 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 respectively in the following manner:

[0105] Step 4.1, calculate the capacity curve of the long-range aircraft, the calculation method is: according to the maximum value of the ordinate and the maximum value of the abscissa of the PL-R diagram, select the maximum range value MaxRange and the maximum load value MaxPayload of the long-range aircraft, calculate the capacity curve of the long-range aircraft through the range calculation formula and the calculation formula of the fuel required for a fixed range, and judge whether the capacity curve meets the coverage condition, that is, whether it covers all the data points in the PL-R diagram. If it is judged that it can be covered, the capacity curve is determined as the capacity curve of the long-range aircraft; otherwise, the capacity curve is adjusted by increasing the maximum load value MaxPlayload until the calculated capacity curve of the long-range aircraft meets the coverage condition;

[0106] Step 42, calculating the capacity curves of conventional and short-range aircraft, and calculating 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 conventional and short-range aircraft, respectively calculating the capacity curves of the conventional and short-range aircraft by using the range calculation formula and the calculation formula of the fuel required for the fixed range; respectively determining the flight missions of the three types of aircraft in the PL-R diagram according to the capacity curves of the three types of aircraft, and calculating the total fuel consumption according to the objective function 1 in step 3;

[0107] Step 43, using an optimization algorithm, taking the total fuel consumption as the optimization target, and taking the maximum range value MaxRange and the maximum load value MaxPayload of conventional and short-range aircraft as variables for optimization, until the total fuel consumption meets the optimization stop condition; wherein, there are two methods for determining the optimization stop condition: fixing the number of optimization iterations, and the difference between the total fuel consumption calculated by two iterations is less than a set threshold.

[0108] Step 5, taking into account the quality changes of the flight control subsystem, hydraulic subsystem, and power subsystem in the aircraft management system, calculate the total fuel consumption of the three types of aircraft. The specific calculation process of step 5 may 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 load value MaxPayload of the three types of aircraft determined in step 41 and step 42, by using a calculation formula for the fuel required for the fixed range, 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;

[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 electric power subsystem, and calculating the maximum take-off weight of the three types of aircraft in combination with 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 according to the maximum take-off weight of the three types of aircraft and the calculated capacity curves of 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 is: the difference between the fuel mass carried by the three types of aircraft obtained by two iterative calculations is less than a set threshold.

[0111] Step 53, based on the fuel masses carried by the three types of aircraft obtained by convergence calculation, calculate the total fuel consumption of the three types of aircraft in consideration of the mass changes of the flight control subsystem, the hydraulic subsystem, and the electric power subsystem in the aircraft management system.

[0112] For the optimization target 2 determined in step 2, the optimization target 2 is optimized through the following steps 6 to 7, which specifically include:

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

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

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

[0116] After optimizing the above optimization target 1 and optimization target 2, the method provided in this embodiment further includes the following steps:

[0117] Step 8, forming a feasible solution for selecting a system architecture of multiple subsystems through genetic algorithm optimization;

[0118] The implementation method of this step includes: setting the probability of selection, crossover and mutation, population size and number of iterations; generating multiple individuals in the initial population according to multiple sets of design variables, calculating the objective function 1 and objective 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, crowding calculation); calling selection, crossover and mutation functions to form new individuals; calculating the values ​​of objective function 1 and objective function 2 of the new individuals, sorting the current population and the new individuals, and updating the population according to the sorting results; and then calling selection, crossover and mutation functions again to form new individuals until the convergence conditions are met to form a feasible solution set for the system architecture selection of multiple subsystems; the convergence condition of this step is: number of iterations.

[0119] Step 9, generating a Pareto frontier based on the feasible solution set of the system architecture selection of the multi-subsystem obtained in step 8, and determining the final selected system architecture, including: determining the Pareto frontier (i.e., a solution that cannot improve the value of one objective function without reducing the value of the other objective function) for the feasible solution set of objective function 1 and objective function 2. The Pareto frontier represents the trade-off between the achievable limit and the optimization goal. The specific solution to be selected (which architecture combination form and equipment selection) depends on the specific needs and preferences of the decision maker. For example, if the decision maker pays more attention to the operating cost (fuel consumption), he may tend to choose the solution close to the left side of the frontier (the horizontal axis represents fuel consumption); if the decision maker pays more attention to the maintenance cost (basic system reliability), he may choose the solution close to the bottom of the frontier (the vertical axis represents basic reliability).

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

[0121] Implementation Example 1:

[0122] The values ​​of the design variables are:

[0123] Design variable 1, "FCS Power Supply" takes values ​​of 0 and 1. "0" means all hydraulic actuators are selected, and "1" means all electro-hydraulic actuators are selected.

[0124] Design variable 2, “Hydraulic Power Source” takes values ​​of 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+1EMP+1EMP.

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

[0126] The optimization results obtained are:

[0127] First, there are duplicate solutions among the 100 solutions obtained in the last generation of optimization. For example, the second and third solutions are the same, and the first and fourth 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 frontier. Figure 3 , which is a schematic diagram of the Pareto front result in implementation example 1 of the present invention.

[0128] Next, the 20 unique solutions are marked in the Pareto front diagram. For example, for solution No. 1 in the figure, although it performs well in fuel consumption (objective function 1), it is relatively high in reliability (objective function 2).

[0129] Since all 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 have achieved a good balance between fuel consumption and reliability, so they can be used as alternative solutions. For example, compared with solution 7, solution 8 can significantly improve reliability by only slightly increasing fuel consumption; similarly, compared with solution 14, solution 13 can significantly reduce fuel consumption at the expense of a small amount of reliability. Therefore, from a compromise perspective, solutions 8 to 13 are better choices. Taking an example, the architecture selection corresponding to Solution 8 is: long-range aircraft: the flight control subsystem uses electric actuators; the hydraulic subsystem selects 1EDP+1EMP+1RAT+1EDP+1EMP; the power subsystem selects a cross-frequency AC power supply system; conventional aircraft: the flight control subsystem uses hydraulic actuators; the hydraulic subsystem selects 1EDP+1EMP+1EMP+1EMP+1EMP; the power subsystem selects a 270V high-voltage mainstream power supply system; short-range aircraft: the flight control subsystem uses electric actuators; the hydraulic subsystem selects 1EDP+1EMP+1RAT+1EDP+1EMP; the power subsystem selects a cross-frequency AC power supply system.

[0130] Implementation Example 2:

[0131] The values ​​of the design variables are:

[0132] Design variable 1, "FCS Power Supply" takes values ​​of 0, 1, 2, and 3. "0" indicates centralized hydraulic braking. "1" indicates centralized electro-hydraulic braking. "2" indicates distributed hydraulic braking. "3" indicates distributed electro-hydraulic braking.

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

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

[0135] Design variable 3, "Power System Architecture", takes values ​​of 0, 1, and 2. "0" indicates a constant speed and frequency AC power supply system, including the main power supply, secondary power supply, auxiliary power supply, emergency power supply, generator transformer rectifier, etc. 1 indicates an alternating frequency AC power supply system, including the main power supply, secondary power supply, auxiliary power supply, and emergency power supply, etc. "2" is a 270V high-voltage mainstream power supply system, including the main power supply, auxiliary power supply, secondary power supply, etc.

[0136] The optimization results obtained are:

[0137] First, there are duplicate solutions in the 200 solutions obtained by optimization in the last generation. After merging the same solutions, it is found that there are actually only 39 unique solutions that constitute the Pareto frontier. Figure 4 , which is a schematic diagram of the Pareto front result in implementation example 2 of the present invention.

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

[0139] Since all 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 11 to 29 have achieved a good balance between fuel consumption and reliability, so they can be used as alternative solutions. For example, compared with solution 10, solution 11 can significantly improve reliability by only slightly increasing fuel consumption; similarly, compared with solution 30, solution 29 can significantly reduce fuel consumption at the expense of a small amount of reliability. Therefore, from a compromise point of view, solutions 11 to 29 are better choices. For example, for long-range aircraft: the flight control subsystem uses distributed electro-hydraulic braking; the hydraulic subsystem uses a pressure of 35MPA, and the configuration is: hydraulic source A1EDP, hydraulic source B1EMP+1RAT, hydraulic source C1EDP+1EMP; the power subsystem uses an alternating-frequency AC power supply system. Conventional aircraft: The flight control system uses distributed hydraulic brakes; the hydraulic subsystem uses a pressure of 35MPA, and the configuration is: hydraulic source A1EDP+1EMP, hydraulic source B2EMP+1RAT, hydraulic source C1EDP+1EMP; the power subsystem uses a 270V high-voltage mainstream power system. Short-range aircraft: The flight control subsystem uses distributed hydraulic brakes; the hydraulic subsystem uses a pressure of 35MPA, and the configuration is: hydraulic source A1EDP, hydraulic source B1EMP+1RAT, hydraulic source C1EDP+1EMP; the power subsystem uses an alternating-frequency AC power system.

[0140] Although the embodiments disclosed in the present invention are as above, the contents are only embodiments adopted to facilitate understanding of the present invention and are not intended to limit the present invention. Any technician in the field to which the present invention belongs can make any modifications and changes in the form and details of implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A multi-subsystem integrated system architecture design optimization method, characterized in that: The multiple subsystems include at least a flight control subsystem, a hydraulic subsystem, and a power subsystem of the aircraft, and the system architecture design optimization method includes: Step 1, determine the design variables, including: determine the various types of actuators used in the flight control subsystem, determine the various types of forms selected by the hydraulic subsystem, and determine the various power supply forms of the power subsystem; Step 2, determining the optimization target, including: for the same type of serialized aircraft, including the following three types: conventional, short-range and long-range; based on the requirements for operating costs and maintenance costs in the design of serialized aircraft, determining at least one optimization target that makes the operating costs and maintenance costs meet the revenue requirements; Step 3, optimizing each optimization target determined in step 2, including: constructing an objective function for each optimization target, solving each objective function using multiple sets of design variables, and obtaining a solution corresponding to each objective function under the multiple sets of design variables; Step 4, comprehensively process the corresponding solutions of multiple optimization objectives under multiple sets of design variables to obtain feasible solutions for the system architecture selection of multiple subsystems and determine the final selected system architecture.

2. The multi-subsystem integrated system architecture design optimization method according to claim 1, characterized in that: The step 1 comprises: Step 11, determining multiple selection forms of actuators used by the flight control subsystem, including: selection form 1, all using electric actuators; selection form 2, all using hydraulic actuators; selection form 3, partially using electric actuators and partially using hydraulic actuators; Step 12, determining multiple selection forms of the hydraulic subsystem according to the multiple hydraulic sources of the hydraulic subsystem and the type of pump used; Step 13, determining multiple power supply forms of 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 multi-subsystem integrated system architecture design optimization method according to claim 2, characterized in that: The step 12 comprises: According to the three hydraulic sources used by the hydraulic subsystem, combined with three types of pumps, by configuring each hydraulic source with a pump used independently or in combination, multiple selection forms of the hydraulic subsystem in step 12 are formed, wherein the three types of pumps include an engine driven pump EDP, an electric pump EMP, and a ram air turbine RAT; the three types of selection forms of the hydraulic subsystem determined in step 12 include: Selection form 1: Hydraulic source A: 1EDP; Hydraulic source B: 1EMP+1RAT; Hydraulic source C: 1EDP+1EMP; Selection form 2: Hydraulic source A: 2EDP+1EMP+1RAT; Hydraulic source B: 1EDP+1EMP; Hydraulic source C: 1EDP+1EMP; Selection form 3: Hydraulic source A: 1EDP+1EMP; Hydraulic source B: 1EMP; Hydraulic source C: 1EDP+1EMP.

4. The multi-subsystem integrated system architecture design optimization method according to claim 3, characterized in that: The step 2 comprises: Step 21, based on the airline's operating cost requirements, the total fuel consumption is calculated based on the coverage load-range-frequency statistical chart, and the total fuel consumption is used as the first optimization target; Step 22, based on the aircraft maintenance cost requirement, select system basic reliability as the second optimization objective.

5. The multi-subsystem integrated system architecture design optimization method according to claim 4, characterized in that: The optimization process for the optimization target 1 in step 3 includes: Step A1, constructing objective function 1 for optimization objective 1, including: constructing a total fuel consumption objective function, taking the total fuel consumption objective function covering the load-range-frequency statistical graph as objective function 1; Step A2, calculating the capability curves and total fuel consumption of the three types of aircraft without considering the quality changes of the flight control subsystem, hydraulic subsystem, and electrical subsystem; Step A3, calculating the total fuel consumption of the three types of aircraft by taking into account the mass changes of the flight control subsystem, hydraulic subsystem, and electrical subsystem.

6. The multi-subsystem integrated system architecture design optimization method according to claim 5, characterized in that: The step A1 comprises: Step A1-1, obtaining a load-range-frequency statistical diagram, i.e., a PL-R diagram; Step A1-2, taking the total fuel consumption objective function of the three types of aircraft covering the PL-R diagram as the objective function 1 of the optimization objective 1, expressed as: Among them, M represents the total number of flights in the PL-R diagram, M1 represents the number of flights waiting to be flown by long-range aircraft in the PL-R diagram, M2 represents the number of flights waiting to be flown by conventional aircraft in the PL-R diagram, and M3 represents the number of flights waiting to be flown by short-range aircraft in the PL-R diagram; Flight fuel(i) represents the fuel consumption of each type of aircraft flying the i-th flight.

7. The multi-subsystem integrated system architecture design optimization method according to claim 5, characterized in that: The calculation method in step A2 is: Based on the Breguet range calculation formula and the balance relationship between the aircraft's lift and gravity, thrust and drag, a discrete cruise range calculation formula and a calculation formula for the fuel required for a fixed range were established, and then the capacity curves of the three types of aircraft were determined, and the total fuel consumption of the three types of aircraft was calculated.

8. The multi-subsystem integrated system architecture design optimization method according to claim 7, characterized in that: The step A2 comprises: Step A2-1, calculating the capability curve of the long-range aircraft, the calculation method is as follows: according to the maximum value of the ordinate and the maximum value of the abscissa of the PL-R diagram, selecting the maximum range value MaxRange and the maximum load value MaxPayload of the long-range aircraft, calculating the capability curve of the long-range aircraft by using the range calculation formula and the calculation formula of the required fuel for a fixed range, judging whether the capability curve meets the coverage condition, that is, whether it covers all the data points in the PL-R diagram, if it is judged that it can cover, then the capability curve is determined as the capability curve of the long-range aircraft; otherwise, adjusting the capability curve by increasing the maximum load value MaxPlayload until the calculated capability curve of the long-range aircraft meets the coverage condition; Step A2-2, calculating the capacity curves of conventional and short-range aircraft, and calculating 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 conventional and short-range aircraft, respectively calculating the capacity curves of the conventional and short-range aircraft by using the range calculation formula and the calculation formula of the fuel required for the fixed range; respectively determining the flight missions of the three types of aircraft in the PL-R diagram according to the capacity curves of the three types of aircraft, and calculating the total fuel consumption according to the objective function 1 in step 3; Step A2-3, using an optimization algorithm, taking total fuel consumption as the optimization target, and taking the maximum range value MaxRange and the maximum load value MaxPayload of conventional and short-range aircraft as variables for optimization, until the total fuel consumption meets the optimization stop condition; wherein, there are two methods for determining the optimization stop condition: fixing the number of optimization iterations, and the difference in total fuel consumption calculated by two iterations is less than a set threshold.

9. The multi-subsystem integrated system architecture design optimization method according to claim 5, characterized in that: The step A3 comprises: Step A3-1, calculating the fuel mass carried by the three types of aircraft, comprising: according to the maximum range value MaxRange and the maximum load value MaxPayload of the three types of aircraft determined in step A2-1 and step A2-2, by using a calculation formula for the fuel required for the fixed range, 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; 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, and calculating the maximum take-off weight of the three types of aircraft in combination with 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 according to the maximum take-off weight of the three types of aircraft and the calculated capacity curves of 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 is: the difference between the fuel mass carried by the three types of aircraft obtained by two iterative calculations is less than a set threshold value; Step A3-3, based on the fuel masses carried by the three types of aircraft obtained by 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, the hydraulic subsystem, and the electric subsystem; Step A3-4, by repeatedly executing step A3-2 and step A3-3, and by reinitializing the values ​​of the design variables of the flight control subsystem, the hydraulic subsystem, and the electric power subsystem in step A3-2, the total fuel consumption under multiple sets of different design variable values ​​is obtained.

10. The multi-subsystem integrated system architecture design optimization method according to claim 4, characterized in that: The optimization process for optimization target 2 in step 3 includes: Step B1, constructing objective function 2 for optimization objective 2, including: constructing a system basic reliability objective function, that is, a whole system reliability function formed by connecting the flight control subsystem, hydraulic subsystem, and power subsystem of the three types of aircraft in series as the system basic reliability objective function; Step B2, calculating the basic reliability of the system, includes: for the flight control subsystem, hydraulic subsystem, and power subsystem of the three types of aircraft, substituting the corresponding equipment failure rate data under multiple sets of design variables into objective function 2 for calculation, and obtaining the basic reliability of the system corresponding to each set of design variables.

11. The system architecture design optimization method for multi-subsystem integration according to any one of claims 1 to 10, characterized in that: The step 4 comprises: Step 41, forming a feasible solution set for selecting a system architecture of multiple subsystems through genetic algorithm optimization; Step 42, generating a Pareto frontier based on the feasible solution set for the system architecture selection of the multiple subsystems obtained in step 42, and determining the final selected system architecture.

12. An integrated system of multiple subsystems, characterized in that: The multiple subsystems of the integrated system include at least the aircraft's flight control subsystem, hydraulic subsystem and power subsystem; the system architecture design optimization method for the multi-subsystem integration described in any one of claims 1 to 11 is used to obtain the selection form of the architecture of each subsystem in the integrated system.

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