Forward design method and design system for power supply architecture of aircraft power supply system and aircraft power supply system

Abstract

The invention relates to the technical field of aviation electrical system design, and provides a forward design method and design system for a power supply architecture of an aircraft power supply system and the aircraft power supply system.The method comprises the steps that a multi-target optimization model with the total weight and total loss of the power supply architecture as optimization targets and the power supply reliability of the system as a constraint condition is established; solving the multi-objective optimization model by adopting an intelligent optimization algorithm by taking the number of bus bars, the number of converters and an electrical connection relationship among power grid nodes in the power supply architecture as optimization variables, and generating a candidate power supply architecture; and verifying the candidate power supply architecture, and outputting a power supply system power supply architecture meeting a verification condition. According to the method, the forward design process of the architecture is achieved based on the intelligent optimization algorithm, the architecture design efficiency is effectively improved, manpower and time cost are saved, and the design method has universality and can be subsequently used for architecture optimization design of power supply systems of various models.

Description

Technical Field

[0001] This invention relates to the field of aviation electrical system design technology, and in particular to a forward design method, design system, and aircraft power system for an aircraft power system power supply architecture. Background Technology

[0002] The aircraft power system is one of the most critical systems in modern aircraft, responsible for providing reliable and high-quality electrical power to all aircraft equipment. Its power supply architecture design (including busbar configuration, converter setup, and electrical connections) directly impacts the weight, efficiency, reliability, and safety of the entire system. Traditional aircraft power system architecture design relies heavily on engineers' experience, employing a "reference to existing aircraft models - partial modifications - iterative verification" approach. This method suffers from the following significant problems: 1. High dependence on experience and lack of systematicity: Design quality is highly correlated with the engineer's personal experience, making it difficult to guarantee that the optimal solution is found globally or near globally.

[0003] 2. Single design indicators, difficult to coordinate: often focusing on meeting single hard constraints such as power supply reliability, while making it difficult to comprehensively weigh and optimize multiple indicators that directly affect aircraft performance and operating costs, such as weight and losses.

[0004] 3. Long iteration cycle and low efficiency: The design process requires a lot of manual adjustment and simulation verification. The topology design and the reconfiguration strategy design under fault conditions are often disconnected, resulting in slow design iteration and high cost.

[0005] 4. Lack of forward design capability: Difficulty in starting from top-level requirements and automatically generating optimized architecture solutions that meet multiple constraints and objectives; in other words, a lack of systematic "forward design" methodology. With the development of more-electric / all-electric aircraft, the number and power of airborne electrical equipment have increased significantly, and the power system architecture has become increasingly complex. Traditional design methods are no longer sufficient to meet the comprehensive design requirements of high efficiency, high reliability, and lightweight design. Therefore, there is an urgent need for a forward design method that can automatically and intelligently complete the multi-objective collaborative optimization of the power supply architecture of the power system. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the present invention aims to provide a forward design method, design system, and aircraft power system for power supply architecture. The core of this method is to model the power supply architecture design as a multi-objective optimization problem and use intelligent optimization algorithms to automatically search for the optimal solution. At the same time, the search for reconfiguration strategies under fault conditions is integrated into the topology optimization process to achieve integrated design.

[0007] The present invention adopts the following technical solution: On one hand, the present invention provides a forward design method for the power supply architecture of an aircraft power system, comprising the following steps: Establish a multi-objective optimization model with the total weight and total loss of the power supply architecture as optimization objectives and the system power supply reliability as a constraint. Using the number of busbars, the number of converters, and the electrical connections between grid nodes in the power supply architecture as optimization variables, an intelligent optimization algorithm is used to solve the multi-objective optimization model to generate candidate power supply architectures. The candidate power supply architecture is verified, and a power supply architecture that meets the verification conditions is output.

[0008] In addition to any of the possible implementations described above, another implementation is provided in which a path search algorithm is integrated in the step of solving the problem using an intelligent optimization algorithm, so as to simultaneously determine the power supply path under normal operating conditions and the power supply reconfiguration path and strategy under preset fault conditions when searching for the electrical connection relationship.

[0009] In addition to any of the possible implementations described above, another implementation is provided that, before establishing the multi-objective optimization model, includes a requirement and parameter input step, specifically including: determining the load power requirements of each voltage level and the importance of the busbars connected to each load based on load statistical analysis; and determining the power supply system, energy type and quantity, and reliability parameters of each component.

[0010] In addition to any of the possible implementations described above, another implementation is provided in which the importance of the busbars includes at least critical busbars and general busbars; the power supply system includes voltage levels and grid configuration; and the reliability parameters of each component include failure rate.

[0011] In addition to any of the possible implementations described above, another implementation is provided in which the total weight calculation model of the power supply architecture in the optimization objective is: Where G is the total weight of the power supply architecture, i represents node i, j represents node j, and when i=j, G ij G represents the weight of device i at node i. When i ≠ j, G ij This represents the total weight of the contactor and converter between nodes i and j; The total loss calculation model is as follows: Where L represents the total power supply architecture loss, i represents node i, j represents node j, and when i=j, L ij L represents the loss of device i when i ≠ j. ij This represents the total loss of the contactor and converter between nodes i and j.

[0012] In addition to any of the possible implementations described above, another implementation is provided in which the power supply reliability constraints in the constraints include at least: the failure rate of the entire aircraft power system is not higher than a first threshold, the power supply failure rate of important busbars is not higher than a second threshold, and the power supply failure rate of general busbars is not higher than a third threshold, wherein the second threshold is lower than the third threshold.

[0013] In addition to any of the possible implementations described above, another implementation is provided in which the electrical connection relationship is described using a node adjacency matrix based on graph theory, wherein the element values ​​in the node adjacency matrix represent the connection state and power flow direction between the corresponding nodes.

[0014] In addition to any of the possible implementations described above, another implementation is provided in which the path search algorithm is a breadth-first search algorithm or a depth-first search algorithm; and the intelligent optimization algorithm is a multi-objective evolutionary optimization algorithm.

[0015] On the other hand, the present invention also provides a forward design system for an aircraft power system architecture to implement the above-mentioned method, the system comprising: The demand and parameter input module, based on load statistical analysis, determines the load power demand at each voltage level and the importance of the busbars connected to each load; and determines the power supply system, energy type and quantity, and reliability parameters of each component. The model building module is used to build a multi-objective optimization model with weight and loss as optimization objectives and power supply reliability as a constraint. The optimization solution module inputs the requirements and parameters into the multi-objective optimization model, and solves the model with the number of busbars, the number of converters, and the electrical connection relationship as optimization variables to obtain the candidate power supply architecture; The verification output module is used to verify the candidate power supply architectures generated by the solution and output the final solution.

[0016] On the other hand, the present invention also provides an aircraft power system, the power supply architecture of which is designed using the above-described method.

[0017] The beneficial effects of this invention are as follows: 1. Achieve forward automated design: It changes the experience-dependent "reverse modification" mode and can automatically generate optimized architecture solutions from top-level requirements, improving the scientific and systematic nature of the design.

[0018] 2. Achieve multi-objective comprehensive optimization: Incorporate multiple key design indicators such as weight, loss, and reliability into the optimization model simultaneously, and use multi-objective optimization algorithms to automatically find their optimal balance point (Pareto solution set), which helps to obtain an architecture with better overall performance.

[0019] 3. Improve design efficiency and quality: Through intelligent algorithms, the design cycle is greatly shortened by automatically finding the best design in a huge design space. It may also discover excellent topologies that are difficult for humans to think of, thereby improving design quality.

[0020] 4. Coupled Topology and Reconfiguration Design: The innovative design embeds the power supply path search and reconfiguration strategy generation under fault conditions into the topology optimization loop, ensuring that the designed architecture not only has excellent static performance, but also has inherent fault tolerance and reconfiguration capabilities, thereby improving the maturity and reliability of the design.

[0021] 5. Possesses good versatility and scalability: The framework of this method is universal. By adjusting the input parameters, optimizing the objectives and constraints, it can be applied to the design of aircraft power system architectures for different aircraft models and power supply systems, and has broad application prospects. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating the forward design method for the power supply architecture of an aircraft power system provided in an embodiment of the present invention.

[0023] Figure 2 The diagram shown is the overall flowchart of the forward design method for the power supply architecture of the aircraft power system in this embodiment. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and the accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0025] The accompanying drawings illustrate a layer structure according to an embodiment of the present invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0026] Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0027] In the description of this invention, it should be noted that the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0028] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0029] like Figure 1 As shown in the figure, an embodiment of the present invention provides a forward design method for the power supply architecture of an aircraft power system based on an intelligent optimization algorithm, comprising the following steps: S1. Requirements and Parameter Input: Based on the overall aircraft design and load layout, perform load statistical analysis to determine the load power requirements at each voltage level and identify the importance of the busbars connected to each load (e.g., critical busbars, general busbars). Simultaneously, determine the top-level design parameters of the power system, including the power supply system (voltage, configuration), energy type and quantity (engine, APU, battery, etc.), and the reliability parameters (e.g., failure rate) and basic performance parameters of various components such as generators, converters, and contactors.

[0030] S2. Optimization Model Construction: Establish a multi-objective optimization model for the power supply architecture. Optimization objectives typically include minimizing the total weight and total losses of the power supply architecture. Constraints must include at least power supply reliability constraints (such as the total system failure rate and upper limits for the failure rate of critical / general busbars). Optimization variables are the topology parameters of the power supply architecture, mainly including the number of busbars, the number of converters, and the electrical connection matrix describing the connection relationships between all power sources, converters, and busbars.

[0031] S3. Intelligent Optimization Solution: A multi-objective intelligent optimization algorithm (such as NSGA-III, LSMOF, etc.) is used to solve the above model. During the algorithm solution process, especially when evaluating the fitness of each candidate architecture (i.e., a set of optimization variable values), its weight, losses, and reliability need to be calculated. The reliability calculation needs to determine whether the system can continue to supply power to critical loads through reconfiguration under various preset fault conditions. To this end, this step integrates a path search algorithm (such as Breadth-First Search, BFS) to automatically search for power supply paths under normal operation and fault conditions within a given candidate architecture topology, determine whether reliability constraints are met, and generate corresponding fault reconfiguration strategies. This step ultimately outputs a set of Pareto optimal candidate architectures that satisfy the constraints.

[0032] S4. Verification and Decision Output: Further detailed verification of the candidate architecture set obtained from the optimization solution is performed, including constraint verification based on a more accurate model (weight, loss, failure rate) and dynamic simulation verification (verifying power outage time, load switching transient processes, etc.). Finally, designers can select one or more final architecture schemes from the Pareto frontier according to engineering preferences for output.

[0033] Example like Figure 2 As shown, this embodiment takes the preliminary design of a hybrid power supply system of 270V high-voltage DC and 28V low-voltage DC for a certain type of civil aircraft as an example to illustrate the specific implementation process of this method.

[0034] Step S1: Requirements and Parameter Input First, collect and analyze the power requirements, operating voltage, operating phase (e.g., takeoff, cruise, landing), and importance level of each aircraft electrical device. The results show that the total power of the 270V high-voltage DC (HVDC) load is approximately 150kW, and the total power of the 28V low-voltage DC (LVDC) load is approximately 25kW. The flight control computer and core avionics equipment are defined as critical loads and connected to important busbars; other equipment is connected to general busbars.

[0035] The top-level design parameters are determined as follows: The power supply system adopts a hybrid architecture of "two-way HVDC + multiple-way LVDC" commonly used in twin-engine aircraft. The energy source includes two generators driven by the main engines (GEN1, GEN2) and one auxiliary power unit (APU) generator. The baseline failure rate (λ), power-to-weight ratio (kg / kW), and efficiency (η) parameters for each component are obtained from the component database or supplier data.

[0036] Step S2: Optimize model construction 1. Optimize variable definitions: X_b: Number and type of HVDC and LVDC buses (important / general). Factors to consider in determining the importance of a bus include: its location in the power supply network, the diversity and reliability of the power sources connected, and the indispensability of the load it serves to flight safety and mission.

[0037] X_c: Number and rated power rating of DC-DC converters.

[0038] X_conn: Electrical connection matrix. Generators, converters, and busbars are abstracted as network nodes, and the connection relationship is represented by an adjacency matrix A. If there is a direct electrical connection between node i and node j (such as through a contactor or cable), then A(i,j) = 1, -1, 2, and the cable parameters of that connection can be associated; otherwise, it is 0.

[0039] Node adjacency matrix: in, This indicates the connection relationship between node i and node j, and also the power flow direction between the nodes: .

[0040] 2. Optimize the objective function: Min Weight; Min Loss: P_{loss,total}; The weight and losses of each component are functions of its power and operating point, and can be obtained by searching a database or calculating a model.

[0041] 3. Constraints: Reliability constraints: Overall system failure rate < 1.33E-3; critical bus failure rate < 1.0E-4; general bus failure rate < 1.0E-3.

[0042] Weight constraint: Total weight of the power system < 500 kg (example value).

[0043] Loss constraint: Total loss under rated operating conditions < 15 kW (example value).

[0044] Physical and logical constraints: such as generator power limit, converter input and output voltage matching, and prohibition of ring power supply.

[0045] Step S3: Intelligent Optimization Solution This step uses the NSGA-III algorithm as the multi-objective optimization solver and embeds a breadth-first search (BFS) algorithm for reliability assessment.

[0046] 1. Initialization: Randomly generate an initial population of a certain size, with each individual representing a set of architectural parameters (X_b, X_c, X_conn).

[0047] 2. Fitness Assessment (Core): Perform the following operations for each individual (candidate architecture) in the population: a. Topology analysis: Construct a specific power supply network diagram based on its X_conn matrix.

[0048] b. Calculate static metrics: Based on X_b, X_c and the component model, calculate the estimated total weight and total loss of the architecture.

[0049] c. Reliability Assessment (Integrated BFS): For a predefined set of faults (e.g., "GEN1 failure", "short circuit on an HVDC feeder"), run the BFS algorithm on the current topology to search for a valid power supply path from the available power source to each critical load. By statistically analyzing the power loss of loads under all fault scenarios and combining the component failure rates, calculate the failure rates of the system and each busbar. If any reliability constraint is not met, assign a "penalty value" to that individual or mark it as an infeasible solution.

[0050] d. Output fitness: The calculated weight and loss are used as target values, and whether the reliability is met is used as the constraint judgment criterion, and the output is given to the NSGA-Ⅲ algorithm.

[0051] 3. Algorithm Iteration: The NSGA-Ⅲ algorithm selects, crosses over, and mutates based on fitness to generate a new generation of population. Step 2 is repeated until the preset number of iterations is reached.

[0052] 4. Output Results: After the algorithm finishes, it outputs the Pareto optimal solution set. These solutions form a front line on the weight-loss plane, and each point on the line represents an architectural solution that cannot be improved on both objectives simultaneously under the existing constraints.

[0053] Step S4: Verification and Decision Output Select 3-5 representative candidate architectures from the Pareto solution set (e.g., lightest solution, minimum loss solution, equilibrium solution). Then, evaluate these solutions as follows: Detailed modeling and simulation: Build more detailed models in MATLAB / Simulink or dedicated power system simulation software to simulate dynamic processes such as load switching, engine idle-cruise switching, and fault reconfiguration, and accurately verify dynamic indicators such as power outage time and voltage transients.

[0054] Project review: A comprehensive evaluation is conducted, taking into account factors such as cabling complexity, maintainability, and thermal management.

[0055] Decision output: Finally, based on simulation results and engineering judgment, the design team selects the final power supply architecture scheme and its corresponding fault reconfiguration logic table from the candidate schemes.

[0056] System Implementation Examples A forward design system for an aircraft power system architecture that implements the above method includes: The demand and parameter input module is used to input the load power demand for each voltage level and the importance of the busbars connected to each load; and to input the power supply system, energy type and quantity, and reliability parameters of each component. The model building module is used to build a multi-objective optimization model with weight and loss as optimization objectives and power supply reliability as a constraint. The optimization solution module inputs the requirements and parameters into the multi-objective optimization model, and solves the model with the number of busbars, the number of converters, and the electrical connection relationship as optimization variables to obtain the candidate power supply architecture; The verification output module is used to verify the candidate power supply architectures generated by the solution and output the final solution.

[0057] The above description of the embodiments is only for the purpose of helping to understand the method and core idea of ​​this application; at the same time, for those skilled in the art, there will be changes in the specific implementation and application scope based on the idea of ​​this application. Therefore, the content of this specification should not be construed as a limitation of this application.

[0058] Certain terms are used in the specification and claims to refer to specific components. Those skilled in the art will understand that hardware manufacturers may use different names to refer to the same component. This specification and claims do not distinguish components based on differences in name, but rather on differences in function. The terms "comprising" and "including" used throughout the specification and claims are open-ended and should be interpreted as "comprising / including but not limited to". "Approximately" means that within an acceptable margin of error, those skilled in the art can solve the technical problem and substantially achieve the technical effect within a certain margin of error. The following descriptions in the specification are preferred embodiments for carrying out this application; however, these descriptions are for the purpose of illustrating the general principles of this application and are not intended to limit the scope of this application. The scope of protection of this application shall be determined by the appended claims.

[0059] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a product or system comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a product or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the product or system that includes said element.

[0060] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0061] The foregoing description illustrates and describes several preferred embodiments of this application. However, as previously stated, it should be understood that this application is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the application concept described herein through the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of this application should be within the protection scope of the appended claims.

Claims

1. A forward design method for the power supply architecture of an aircraft power system, characterized in that, Includes the following steps: Establish a multi-objective optimization model with the total weight and total loss of the power supply architecture as optimization objectives and the system power supply reliability as a constraint. Using the number of busbars, the number of converters, and the electrical connections between grid nodes in the power supply architecture as optimization variables, an intelligent optimization algorithm is used to solve the multi-objective optimization model to generate candidate power supply architectures. The candidate power supply architecture is verified, and a power supply architecture that meets the verification conditions is output.

2. The forward design method for the power supply architecture of an aircraft power system as described in claim 1, characterized in that, In the step of solving the problem using intelligent optimization algorithms, an integrated path search algorithm is used to simultaneously determine the power supply path under normal operating conditions and the power supply reconfiguration path and strategy under preset fault conditions while searching for the electrical connection relationships.

3. The forward design method for the power supply architecture of an aircraft power system as described in claim 1, characterized in that, Before establishing the multi-objective optimization model, the process also includes demand and parameter input steps, specifically including: determining the load power demand of each voltage level and the importance of the busbars connected to each load based on load statistical analysis; and determining the power supply system, energy type and quantity, and reliability parameters of each component.

4. The forward design method for the power supply architecture of an aircraft power system as described in claim 3, characterized in that, The importance of the busbars includes at least critical busbars and general busbars; the power supply system includes voltage level and power grid configuration; the reliability parameters of each component include failure rate.

5. The forward design method for the power supply architecture of an aircraft power system as described in claim 1, characterized in that, The calculation model for the total weight of the power supply architecture in the optimization objective is as follows: ； Where G is the total weight of the power supply architecture, i represents node i, j represents node j, and when i=j, G ij G represents the weight of device i at node i. When i ≠ j, G ij This represents the total weight of the contactor and converter between nodes i and j; The total loss calculation model is as follows: ； Where L represents the total power supply architecture loss, i represents node i, j represents node j, and when i=j, L ij L represents the loss of device i when i ≠ j. ij This represents the total loss of the contactor and converter between nodes i and j.

6. The forward design method for the power supply architecture of an aircraft power system as described in claim 4, characterized in that, The power supply reliability constraints in the constraints include at least the following: the failure rate of the entire aircraft power system is not higher than a first threshold, the power supply failure rate of important busbars is not higher than a second threshold, and the power supply failure rate of general busbars is not higher than a third threshold, wherein the second threshold is lower than the third threshold.

7. The forward design method for the power supply architecture of an aircraft power system as described in claim 1, characterized in that, The electrical connection relationship is described using a node adjacency matrix based on graph theory. The element values ​​in the node adjacency matrix represent the connection status and power flow direction between the corresponding nodes.

8. The forward design method for the power supply architecture of an aircraft power system as described in claim 2, characterized in that, The path search algorithm is either a breadth-first search algorithm or a depth-first search algorithm; the intelligent optimization algorithm is a multi-objective evolutionary optimization algorithm.

9. A forward design system for an aircraft power system architecture, used to implement the method as described in any one of claims 1-8, characterized in that, The system includes: The demand and parameter input module is used to input the load power demand for each voltage level and the importance of the busbars connected to each load; as well as the power supply system, energy type and quantity, and reliability parameters of each component. The model building module is used to build a multi-objective optimization model with weight and loss as optimization objectives and power supply reliability as a constraint. The optimization solution module inputs the requirements and parameters into the multi-objective optimization model, and solves the model with the number of busbars, the number of converters, and the electrical connection relationship as optimization variables to obtain the candidate power supply architecture; The verification output module is used to verify the candidate power supply architectures generated by the solution and output the final solution.

10. An aircraft power system, characterized in that, The power supply architecture of the aircraft power system is designed using the method described in any one of claims 1-8.

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