Multi-level collaborative prototyping method, system and readable storage medium for aircraft energy management strategy

Abstract

The application discloses a kind of multilevel collaborative prototyping design method, system and readable storage medium of aircraft energy management strategy, belong to avionics electrical design field.The method includes S1 offline simulation modeling and preliminary verification, and establishes and verifies the initial simulation model including multiple systems and energy management strategy;S2 model segmentation and real-time closed-loop verification, the initial model is segmented into controlled object model and control strategy model, and is deployed to different real-time simulation target mechanism to build the first closed-loop verification environment for testing and cross-level result comparison;S3 strategy optimization and hardware-in-the-loop verification, the optimized strategy code is deployed as prototype controller, and the second closed-loop verification environment is built for final verification with real or high-fidelity simulation physical aircraft system.The application realizes the efficient and reliable iteration of control strategy from virtual design to physical integration through hierarchical progressive verification process connected by data link, significantly reduces physical verification risk and cost, shortens development cycle and improves confidence.

Description

Technical Field

[0001] This invention relates to the field of avionics and electrical design and simulation verification technology, and in particular to a multi-level collaborative prototyping method, system and readable storage medium for aircraft energy management strategies. Background Technology

[0002] The aircraft energy management system is one of the core systems ensuring the safe and efficient operation of an aircraft. It is responsible for the comprehensive management and optimization of the generation, storage, distribution, and consumption of various energy sources, including onboard electrical energy, hydraulic energy, and pneumatic energy. The reliability and effectiveness of its control strategy are of paramount importance. Traditional control strategy development and verification mainly rely on pure digital simulation or direct physical bench testing.

[0003] Pure digital simulation is typically conducted in a non-real-time environment. While it allows for rapid algorithm iteration, it cannot accurately simulate the dynamic response, communication latency, and hardware characteristics of real-world systems. The confidence level of simulation results is limited, making it difficult to uncover deep-seated issues related to real-time performance and hardware interfaces. Direct physical bench testing, on the other hand, requires building a complete test environment with expensive equipment such as real generators, loads, and drive stations. This approach has drawbacks such as long construction cycles, high costs, significant safety risks, and poor scalability. Furthermore, it is not suitable for frequent strategy iterations in the early stages of R&D.

[0004] In recent years, hardware-in-the-loop simulation and rapid control prototyping technologies have been introduced into engineering verification. For example, existing technologies disclose single- or semi-physical simulation test schemes for aircraft starting and power generation systems, flight management systems, or power generation controllers. While these schemes improve the realism of verification, they often focus on a specific subsystem or a specific verification level (such as pure software simulation or semi-physical simulation), lacking a comprehensive, multi-level, and integrated collaborative verification framework that spans from top-level strategy design to bottom-level code generation and integration with real hardware. The lack of clarity regarding model consistency, data transfer, and iterative feedback mechanisms between different levels leads to fragmented development processes, and there is still room for improvement in verification efficiency and the depth of strategy optimization.

[0005] Therefore, the industry urgently needs a prototype design method for aircraft energy management strategies that can run through the entire design cycle, achieve a smooth transition from virtual to physical, and support efficient iteration and high-confidence verification of control strategies. Summary of the Invention

[0006] The technical problem solved by this invention: 1. The verification process is fragmented, with offline simulation, real-time testing and physical verification being disconnected. The lack of unified model and data management leads to low iteration efficiency.

[0007] 2. Traditional pure digital simulation has insufficient confidence and is difficult to accurately evaluate the performance of strategies in actual hardware and real-time environments.

[0008] 3. Direct physical verification is costly, risky, and time-consuming, and is not suitable for frequent modifications and verifications in the early stages of R&D.

[0009] 4. Existing semi-physical simulation schemes are mostly aimed at local systems, and lack an integrated verification method that is multi-level and collaborative for the whole machine and multi-energy system.

[0010] To address the aforementioned technical problems, this invention provides a multi-level collaborative prototyping method, system, and readable storage medium for aircraft energy management strategies. Its core idea lies in constructing a three-level verification system that is interconnected by data links and can be iteratively optimized, namely, "offline simulation modeling and preliminary verification", "model segmentation and real-time closed-loop verification", and "strategy optimization and hardware-in-the-loop verification".

[0011] The present invention adopts the following technical solution: On one hand, this invention provides a multi-level collaborative prototyping method for aircraft energy management strategies, comprising the following steps executed sequentially and linked by a data link: S1. Offline simulation modeling and preliminary verification: Establish an initial simulation model that includes flight dynamics, propulsion system, electrical system and energy management strategy, perform non-real-time simulation, and obtain the first verification results; S2. Model Segmentation and Real-time Closed-Loop Verification: The initial simulation model is segmented into a controlled object model and a control strategy model, and deployed to the first real-time simulation target machine and the second real-time simulation target machine respectively. A first real-time closed-loop verification environment is constructed for testing, and a second verification result is obtained. S3. Strategy Optimization and Hardware-in-the-Loop Verification: Based on the second verification result, optimize the control strategy model and deploy the optimized model code on the second real-time simulation target machine as a prototype controller; replace the controlled object model in the first real-time simulation target machine with a real or high-fidelity simulated physical aircraft system, construct a second real-time closed-loop verification environment for final verification, and output the target energy management strategy.

[0012] In addition to any of the possible implementations described above, another implementation is provided in which the "model segmentation" in step S2 is specifically performed as follows: based on the computational complexity and real-time requirements of the model, the part of the initial simulation model that describes the physical dynamic characteristics of the aircraft is designated as the controlled object model, and the energy management part that includes logical judgment and optimization algorithm is designated as the control strategy model.

[0013] In addition to any of the possible implementations described above, a further implementation is provided in which step S2 further includes a cross-level consistency comparison step: comparing the second verification result with the first verification result under the same test stimulus; if the deviation of the key performance indicators exceeds a preset threshold, then the control strategy model is corrected, and a corrected control strategy model is generated for subsequent steps.

[0014] In addition to any of the possible implementations described above, another implementation is provided, wherein the key performance indicators include at least one of the following: power supply bus voltage stability, multi-energy power distribution efficiency, and number of power supply interruptions to key loads.

[0015] In addition to any of the possible implementations described above, another implementation is provided in which, in step S2, the first real-time simulation target machine and the second real-time simulation target machine communicate via an FPGA-based or deterministic real-time Ethernet protocol to ensure the synchronization of simulation steps and the determinism of data interaction.

[0016] In addition to any of the possible implementations described above, another implementation is provided in which "deploying the optimized model code" in step S3 specifically means: using automatic code generation technology, the optimized control strategy model is directly converted from the graphical modeling environment into embedded C code that runs on the real-time target machine.

[0017] In addition to any of the possible implementations described above, another implementation is provided in which the physical aircraft system includes a real aircraft generator controller, power distribution box, battery and load simulation cabinet, and is connected to the prototype controller through a power interface and a signal interface.

[0018] In addition to any of the possible implementations described above, another implementation is provided, wherein the energy management strategy is used to comprehensively manage and optimize the generation, storage, distribution and consumption of at least two of the electrical energy, hydraulic energy and pneumatic energy on the aircraft.

[0019] On the other hand, the present invention also provides a collaborative prototyping system for aircraft energy management strategies to implement the above-described method, comprising: The offline simulation module is used to build an initial simulation model that includes flight dynamics, propulsion system, electrical system and energy management strategy, perform non-real-time simulation, and obtain the first verification results; A real-time simulation platform, including a first real-time simulation target machine and a second real-time simulation target machine, divides the initial simulation model into a controlled object model and a control strategy model, and deploys them to the first real-time simulation target machine and the second real-time simulation target machine respectively, constructs a first real-time closed-loop verification environment for testing, and obtains a second verification result; A rapid prototyping platform is used to integrate the prototype controller with the physical aircraft system, optimize the control strategy model based on the second verification result, and deploy the optimized model code on the second real-time simulation target aircraft as the prototype controller; replace the controlled object model in the first real-time simulation target aircraft with a real or high-fidelity simulated physical aircraft system, construct a second real-time closed-loop verification environment for final verification, and output the target energy management strategy; The data management and analysis module is used to store the first verification result and the second verification result, and to perform cross-level consistency comparison and analysis.

[0020] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0021] The beneficial effects of this invention are as follows: 1. Achieve integrated collaborative design across the entire process: By defining a clear three-tier process and data interface, offline design, real-time verification and hardware integration are seamlessly connected, forming a collaborative workflow that runs through the entire lifecycle of strategy development, which greatly improves development efficiency and the reusability of results at each stage.

[0022] 2. Enhanced Validation Confidence and Depth: Through a progressive "virtual-real-time-physical" validation process, each level is built upon the successful validation of the previous level, and cross-level consistency comparisons ensure the effectiveness of model evolution. Finally, validation is performed in a hardware-in-the-loop environment, significantly improving the confidence of policy validation and enabling earlier and more comprehensive exposure of potential problems.

[0023] 3. Reduced Development Costs and Risks: This method concentrates high-risk physical testing in the final stage, and has already undergone thorough simulation verification in the early stages, thus significantly reducing the risk of equipment damage and safety accidents that may result from direct physical testing. At the same time, it reduces the scale and time required for physical test bench construction, lowering overall development costs.

[0024] 4. Supports complex multi-energy system management: The method of this invention has strong universality and is not only applicable to aircraft electrical systems. Its modeling and verification framework can be extended to verify the comprehensive management strategy of multiple energy forms such as hydraulic and pneumatic systems, meeting the complex needs of modern multi-electric / all-electric aircraft.

[0025] 5. Facilitates iterative optimization: The verification results at each level can be directly fed back to the strategy model, forming a rapid iterative optimization closed loop, which is particularly suitable for the development of complex control strategies that require frequent adjustment and optimization of algorithms. Attached Figure Description

[0026] Figure 1This is a flowchart illustrating the prototype design method for aircraft energy management strategy according to an embodiment of the present invention.

[0027] Figure 2 The diagram shown is a schematic representation of the overall framework of the prototype design system for aircraft energy management strategy provided in this embodiment.

[0028] Figure 3 for Figure 1 The diagram shows the system architecture of the offline simulation modeling stage in the method shown.

[0029] Figure 4 for Figure 1 The diagram shows the system architecture of the real-time closed-loop verification phase in the method shown.

[0030] Figure 5 for Figure 1 The diagram shows the system architecture of the hardware-in-the-loop verification phase in the method shown. Detailed Implementation

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] like Figure 1As shown, an embodiment of the present invention provides a prototype design method for an aircraft energy management strategy, comprising the following steps executed sequentially and linked by a data link: S1. Offline Simulation Modeling and Preliminary Verification: First, based on modeling environments such as MATLAB / Simulink, an initial high-fidelity simulation model was established, encompassing flight dynamics, propulsion system, electrical system, and energy management strategy. This model fully describes the dynamic characteristics of the aircraft in multiple energy domains. In this non-real-time environment, typical flight profiles and fault conditions were injected to preliminarily verify and debug the logical correctness and basic performance of the energy management strategy, obtaining the first verification results (including key performance parameter curves, event logs, etc.).

[0037] S2. Model Segmentation and Real-Time Closed-Loop Verification: The initial simulation model verified in step S1 is intelligently segmented. Based on the model's computational complexity, real-time requirements, and hardware-in-the-loop testing needs, it is segmented into a "controlled object model" (typically including physical models such as flight dynamics, propulsion systems, and electrical systems) and a "control strategy model" (i.e., the energy management algorithm to be verified). Subsequently, the controlled object model is deployed to the first real-time simulation target machine, and the control strategy model is converted into embedded code using automatic code generation technology and deployed to the second real-time simulation target machine. A real-time data link based on a deterministic communication protocol (such as the protocol used by systems like RT-LAB Opal-RT and dSPACE) is established between the two target machines to construct the first real-time closed-loop verification environment. More realistic real-time simulation tests are performed in this environment to obtain the second verification result. A crucial step is cross-level consistency comparison: the second verification result is compared with the first verification result under the same test stimulus to analyze the differences introduced by real-time performance, discretization, and interface latency, and the control strategy model is corrected and optimized accordingly.

[0038] S3. Strategy Optimization and Hardware-in-the-Loop Verification: The control strategy model code optimized in step S2 is deployed on the second real-time simulation target machine, serving as the "prototype controller." Simultaneously, the controlled object model in the first real-time simulation target machine is replaced with real aircraft energy system physical hardware (such as generator controllers, power distribution units, batteries, load simulation cabinets, etc.) or a high-fidelity simulator. Through interface devices such as power amplifiers and signal conditioning boards, the prototype controller is connected to the physical hardware, constructing a second real-time closed-loop verification environment (i.e., a hardware-in-the-loop environment) containing real physical loops. In this final environment, the energy management strategy is tested and fine-tuned under conditions closest to actual operation, verifying its robustness and reliability under complex scenarios such as real hardware interaction, electromagnetic interference, and fault injection. The final output is a target energy management strategy applicable to actual aircraft.

[0039] Example This embodiment uses the development of an energy management strategy for an aircraft electrical system as an example to describe in detail the implementation of the present invention. The core functions of the energy management strategy include: optimizing generator start-up and shutdown and power distribution according to flight phases and load requirements; managing battery charging and discharging; and automatically tiered unloading and reconfiguration of loads in case of failure, to ensure power quality and system survivability. The overall architecture is as follows: Figure 2 As shown.

[0040] Step 1: Offline simulation modeling and preliminary verification like Figure 3 As shown, in this stage, a complete "aircraft-energy system" co-simulation model is built using MATLAB / Simulink software.

[0041] 1. Model Building: Flight dynamics and propulsion system model: Based on aerodynamic data and engine characteristic curves, a simplified model is established that can reflect the power requirements under different flight altitudes, speeds, and attitudes.

[0042] Electrical system model: A detailed model should be constructed including the starter generator (and its controller GCU), transformer rectifier, battery (and its manager BMS), power distribution unit (PDU), and key loads (such as flight control actuators, avionics, environmental control systems, etc.). The load model should be able to simulate its dynamic power characteristics and priorities.

[0043] Energy management strategy model: As the core, the logic of the energy management algorithm is written using Stateflow or Simulink / Embedded Coder modules, including state machines (such as ground, takeoff, cruise, emergency, etc.), power scheduling algorithms, fault detection and handling logic, etc.

[0044] Integrate the above sub-models to form an initial non-real-time co-simulation model that can run on a PC.

[0045] 2. Preliminary verification: Design test cases that cover typical mission profiles (such as takeoff, climb, cruise, descent, and landing) and typical faults (such as single-engine failure, generator failure, and busbar short circuit).

[0046] Simulations are run in the Simulink environment to monitor and record key signals, such as DC bus voltage, generator output current, battery SOC (state of charge), and load switching status, forming the first verification result database.

[0047] Analyze the simulation results, check whether the strategy logic is correct, and make preliminary adjustments to the control parameters (such as voltage threshold, time delay, etc.) until the strategy meets the design requirements at the offline simulation level.

[0048] Step 2: Model Segmentation and Real-time Loop Closure Validation like Figure 4 As shown, the goal of this stage is to transform the offline model into a real-time, runnable distributed system and to perform verification with higher confidence.

[0049] 1. Model segmentation and interface design: The Simulink model from the first step is segmented. The computationally intensive and dynamically responsive controlled object models (flight dynamics, propulsion system, electrical system physical models) are assigned to target machine A (e.g., using the Opal-RT OP5700 real-time simulator).

[0050] Assign the energy management strategy model to target machine B (e.g., using the dSPACE SCALEXIO system). Use the Simulink Coder / Embedded Coder tool to automatically generate C code from the strategy model.

[0051] Define clear I / O interfaces for the two models: the output of target machine A includes controlled quantities such as bus voltage and load current; the input of target machine B is these controlled quantities, and the output is control quantities such as generator excitation command and circuit breaker control signal.

[0052] 2. Real-time system construction and testing: The generated code is downloaded to target machines A and B respectively. The two are connected via a deterministic reflective memory network or high-speed Ethernet (such as IEEE 1588 protocol synchronization) to ensure strict synchronization of the simulation step size (e.g., 100 microseconds), thus constructing the first real-time closed-loop verification environment.

[0053] In this environment, all test cases from the first step are reproduced for real-time simulation. Real-time systems can more realistically simulate the discrete sampling, computational delay, and communication processes of an actual controller.

[0054] 3. Cross-level comparison and strategy optimization: Collect the second verification result. Develop dedicated data comparison and analysis software to automatically compare the second verification result with the first verification result (offline result).

[0055] Key comparisons: Differences in bus voltage drop depth and recovery time between offline and real-time simulations at the same fault injection time; timing deviations of load switching commands, etc.

[0056] If a significant discrepancy is found (such as slower-than-expected protection actions due to communication delays in real-time simulation), the cause is located, and the strategy logic or parameters are modified back to the Simulink model (e.g., adding predictions or adjusting protection settings) to form an optimized strategy model V2.0. This process can be iterated multiple times until the results at both levels are consistent within the engineering tolerance.

[0057] Step 3: Strategy Optimization and Hardware-in-the-Loop Verification like Figure 5 As shown, this phase aims to combine the strategy with real hardware for final verification.

[0058] 1. Hardware-in-the-loop system construction: The final optimized strategy model V2.0 code from the second step is deployed to target machine B, where target machine B acts as the energy management prototype controller.

[0059] Replace a portion of the controlled object model running in target machine A (such as the generator and its controller GCU model) with real GCU hardware. Connect real distribution boxes, power load simulation cabinets, etc., to the system through power interfaces (such as amplifiers) and signal interfaces (such as I / O boards).

[0060] The prototype controller (target machine B)'s I / O board is directly connected to the signal ports of the real GCU and power distribution box via cables, sending control commands and receiving status feedback. Simultaneously, the prototype controller also communicates in real-time with the remaining simulation models in target machine A (such as the aircraft electrical network model and load model). In this way, the prototype controller both controls the real hardware and interacts with the virtual models, forming a hybrid, second real-time closed-loop verification environment that includes real physical loops.

[0061] 2. Final verification and fine-tuning: In this environment, the most rigorous tests are performed. For example, simulating sudden high-power load changes in the power grid, observing the dynamic response of the real GCU under the instructions of the prototype controller, and measuring whether the actual bus voltage fluctuation meets the specifications; injecting short-circuit signals into the real distribution box to verify whether the fault isolation and reconfiguration logic of the prototype controller is executed correctly.

[0062] This stage may uncover issues that were not apparent in the first two virtual simulation steps, such as signal noise, hardware delay characteristics, and electromagnetic compatibility effects. Based on the test results, final engineering fine-tuning (such as filter parameters and pulse width of the drive signal) is performed on the strategy parameters in the prototype controller.

[0063] After thorough verification and fine-tuning in this phase, the strategy code and its parameters in the prototype controller are solidified into the target energy management strategy. This strategy code can then be directly or with minor adaptations ported to a real aircraft energy management computer.

[0064] Through the above three-level, interconnected, and iteratively optimized implementation process, the method of this invention systematically completes the entire process of aircraft energy management strategy development and high-confidence verification from conceptual design and algorithm verification to hardware integration, significantly improving R&D efficiency and reducing engineering risks.

[0065] 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.

[0066] 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.

[0067] 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.

[0068] 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.

[0069] 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 multi-level collaborative prototyping method for aircraft energy management strategies, characterized in that, This includes the following steps, which are executed sequentially and linked by a data chain: S1. Offline simulation modeling and preliminary verification: Establish an initial simulation model that includes flight dynamics, propulsion system, electrical system and energy management strategy, perform non-real-time simulation, and obtain the first verification results; S2. Model Segmentation and Real-time Closed-Loop Verification: The initial simulation model is segmented into a controlled object model and a control strategy model, and deployed to the first real-time simulation target machine and the second real-time simulation target machine respectively. A first real-time closed-loop verification environment is constructed for testing, and a second verification result is obtained. S3. Strategy Optimization and Hardware-in-the-Loop Verification: Based on the second verification result, optimize the control strategy model and deploy the optimized model code on the second real-time simulation target machine as a prototype controller; replace the controlled object model in the first real-time simulation target machine with a real or high-fidelity simulated physical aircraft system, construct a second real-time closed-loop verification environment for final verification, and output the target energy management strategy.

2. The multi-level collaborative prototyping method for aircraft energy management strategy as described in claim 1, characterized in that, The specific method of "model segmentation" in step S2 is as follows: based on the computational complexity and real-time requirements of the model, the part of the initial simulation model that describes the physical dynamic characteristics of the aircraft is defined as the controlled object model, and the energy management part that includes logical judgment and optimization algorithm is defined as the control strategy model.

3. The multi-level collaborative prototyping method for aircraft energy management strategy as described in claim 1, characterized in that, Step S2 also includes a cross-level consistency comparison step: the second verification result is compared with the first verification result under the same test stimulus. If the deviation of the key performance indicators exceeds the preset threshold, the control strategy model is corrected to generate a corrected control strategy model for subsequent steps.

4. The multi-level collaborative prototyping method for aircraft energy management strategy as described in claim 3, characterized in that, The key performance indicators include at least one of the following: power supply bus voltage stability, multi-energy power distribution efficiency, and number of power outages for critical loads.

5. The multi-level collaborative prototyping method for aircraft energy management strategy as described in claim 1, characterized in that, In step S2, the first real-time simulation target machine and the second real-time simulation target machine communicate through an FPGA-based or deterministic real-time Ethernet protocol to ensure the synchronization of simulation steps and the determinism of data interaction.

6. The multi-level collaborative prototyping method for aircraft energy management strategy as described in claim 1, characterized in that, In step S3, "deploying the optimized model code" specifically means: using automatic code generation technology, the optimized control strategy model is directly converted from the graphical modeling environment into embedded C code that runs on the real-time target machine.

7. The multi-level collaborative prototyping method for aircraft energy management strategy as described in claim 1, characterized in that, The physical aircraft system includes a real aircraft generator controller, power distribution box, battery, and load simulation cabinet, and is connected to the prototype controller through power and signal interfaces.

8. The multi-level collaborative prototyping method for aircraft energy management strategy as described in claim 1, characterized in that, The energy management strategy is used to comprehensively manage and optimize the generation, storage, distribution and consumption of at least two of the following energy sources on an aircraft: electrical energy, hydraulic energy and pneumatic energy.

9. A collaborative prototyping system for aircraft energy management strategies to implement the method of any one of claims 1 to 8, characterized in that, include: The offline simulation module is used to build an initial simulation model that includes flight dynamics, propulsion system, electrical system and energy management strategy, perform non-real-time simulation, and obtain the first verification results; A real-time simulation platform, including a first real-time simulation target machine and a second real-time simulation target machine, divides the initial simulation model into a controlled object model and a control strategy model, and deploys them to the first real-time simulation target machine and the second real-time simulation target machine respectively, constructs a first real-time closed-loop verification environment for testing, and obtains a second verification result; A rapid prototyping platform is used to integrate the prototype controller with the physical aircraft system, optimize the control strategy model based on the second verification result, and deploy the optimized model code on the second real-time simulation target aircraft as the prototype controller; replace the controlled object model in the first real-time simulation target aircraft with a real or high-fidelity simulated physical aircraft system, construct a second real-time closed-loop verification environment for final verification, and output the target energy management strategy; The data management and analysis module is used to store the first verification result and the second verification result, and to perform cross-level consistency comparison and analysis.

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

Images