A hardware-in-the-loop test system for an aerospace hybrid electric propulsion system

Abstract

This application provides a hardware-in-the-loop testing system for an aerospace hybrid electric propulsion system, belonging to the technical field of aerospace hybrid electric propulsion systems. Specifically, it includes a hardware platform comprising a joystick, a command parsing computer, a computing board, and a demonstration computer; a digital simulation model of the hybrid electric propulsion system deployed on the computing board; control commands generated by the joystick are sent to the command parsing computer, which parses the control commands and sends them back to the computing board; the digital simulation model of the hybrid electric propulsion system on the computing board calculates the operating status of the digital simulation model in real time based on the control commands and generates operating parameters; the computing board then demonstrates the system by sending the operating parameters to the demonstration computer. This application's processing scheme can efficiently verify the key performance of energy distribution strategies and control systems.

Description

Technical Field

[0001] This application relates to the field of aviation hybrid electric propulsion systems, and more particularly to a hardware-in-the-loop test system for aviation hybrid electric propulsion systems. Background Technology

[0002] Hybrid electric propulsion systems, with their flexibility in energy management and power output, have become an important development direction for future aerospace propulsion systems. They integrate multiple highly coupled subsystems such as turbine power generation, battery energy storage, power transmission and distribution, and propulsion systems, and involve complex control strategies and energy management algorithms. During development, it is essential to fully verify the overall system performance, component coordination characteristics, and the effectiveness of the control logic. Digital simulation alone cannot accurately reflect the interaction between hardware characteristics and system architecture, while bench testing faces limitations such as high cost, long cycle time, and significant safety risks. Summary of the Invention

[0003] In view of this, this application provides a hardware-in-the-loop testing system for an aerospace hybrid electric propulsion system, which solves the problems in the prior art and can efficiently verify the key performance of energy distribution strategies and control systems.

[0004] The hardware-in-the-loop testing system for an aerospace hybrid electric propulsion system provided in this application adopts the following technical solution:

[0005] A hardware-in-the-loop test system for an aerospace hybrid electric propulsion system includes:

[0006] The hardware platform includes a joystick, an instruction parsing computer, computing boards, and a demonstration computer;

[0007] The digital simulation model of the hybrid electric propulsion system includes an energy management sub-model, a turboshaft engine sub-model, a generator sub-model, a battery energy storage sub-model, a DC bus sub-model, an electric motor drive sub-model, and a ducted fan propulsion sub-model. The digital simulation model of the hybrid electric propulsion system runs on the computing board. The Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system is constructed through the MATLAB / Simulink modeling platform. The Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system is converted into C language code and deployed on the computing board to realize the operation of the digital simulation model of the hybrid electric propulsion system on the computing board.

[0008] The control commands generated by the joystick are transmitted to the command parsing computer via USB. The command parsing computer parses the control commands and sends them to the computing board. The hybrid electric propulsion system digital simulation model on the computing board calculates the operating status of the hybrid electric propulsion system digital simulation model in real time based on the control commands and generates operating parameters. The computing board sends the operating parameters to the demonstration computer via UDP communication.

[0009] The demonstration computer is used to display the operating parameters of the digital simulation model of the hybrid electric propulsion system, to display the energy flow and dynamic distribution logic of the digital simulation model of the hybrid electric propulsion system under different working modes, to simulate the complete flight mission profile of the aircraft and to display the real-time flight profile, real-time monitoring data of flight parameters and real-time energy distribution data.

[0010] Optionally, the computing board includes two CPU processing nodes and one NPU processing node. The two CPU processing nodes and the NPU processing node are interconnected via a PCIe bus. Both CPU processing nodes and the NPU processing node communicate with each other via triple-redundancy time-triggered Ethernet.

[0011] Optionally, the energy management sub-model is used to perform simulation calculations and dynamically allocate the output power parameters of the two generator simulation modules in the generator sub-model and the battery simulation module in the battery energy storage sub-model based on the simulated load demand of the motor drive sub-model, the simulated operating state of the DC bus sub-model, and the simulated state of charge of the battery energy storage sub-model. The parameter set configured by the energy management sub-model includes power allocation strategy parameters, upper and lower limit thresholds of the battery state of charge output by the battery energy storage sub-model, energy supply priority coefficients of the generator sub-model and the battery energy storage sub-model, and fault redundancy allocation parameters.

[0012] The turboshaft engine sub-model is used to respond to the simulation control commands of the generator sub-model. It outputs corresponding speed parameters through the built-in fuel regulation simulation module and speed regulation simulation module to provide simulation power drive parameters for the generator sub-model. The parameter set configured in the turboshaft engine sub-model includes the PID parameters of the engine governor, the fuel flow-speed mapping relationship, and the engine maximum speed limit parameters.

[0013] The generator sub-model is used to simulate the mechanical energy parameters of the turboshaft engine sub-model, which are then converted into AC simulation parameters and then into DC simulation parameters via the built-in rectifier simulation module. This provides stable simulated DC power parameters for the DC bus sub-model. The parameter set configured in the generator sub-model includes generator electromagnetic characteristic parameters, stator winding impedance parameters, power factor parameters, generator efficiency curve parameters, rectifier topology parameters, commutation reactance parameters, firing angle control algorithm parameters, generator electromechanical conversion efficiency, and rectifier ripple suppression parameters.

[0014] The battery energy storage sub-model is used to simulate the storage characteristics of stored electrical energy. The battery energy storage sub-model has a built-in conversion simulation module. The conversion simulation module realizes bidirectional simulated power transfer between the battery energy storage sub-model and the DC bus sub-model by simulating a DC / DC converter. The conversion simulation module is also used to respond to the charging and discharging commands of the energy management sub-model and to simulate the voltage stability control of the DC bus sub-model. The parameter set configured by the conversion simulation module includes DC / DC topology parameters, DC / DC conversion efficiency curve parameters, duty cycle control algorithm parameters, battery internal resistance characteristic parameters, and battery charging and discharging rate limit parameters.

[0015] The DC bus sub-model is used to simulate and integrate the DC simulation electrical parameters output by the rectifier simulation module and the simulation electrical parameters output by the converter simulation module, providing unified DC simulation power supply parameters for the motor drive sub-model. The parameter set configured in the DC bus sub-model includes bus equivalent impedance parameters, line loss parameters, and voltage and current sharing control parameters.

[0016] The motor drive sub-model is used to receive the simulation power supply signal of the DC bus sub-model, respond to the operation command and output the simulation mechanical power parameters, and drive the ducted fan propulsion sub-model to complete the simulation operation. The parameter set configured by the motor drive sub-model includes motor electromagnetic parameters, speed control algorithm parameters, efficiency curve parameters, maximum torque or speed limit parameters and stator impedance parameters.

[0017] The ducted fan propulsion sub-model is used to convert the simulated mechanical dynamic parameters output by the electric motor drive sub-model into aerodynamic thrust simulation parameters, thereby realizing the simulation reproduction of the aircraft's power output. The parameter set configured in the ducted fan propulsion sub-model includes fan aerodynamic characteristic parameters, blade efficiency parameters, speed-thrust mapping relationship parameters, maximum thrust limit parameters, and aerodynamic loss function parameters.

[0018] The energy management sub-model, turboshaft engine sub-model, generator sub-model, battery energy storage sub-model, DC bus sub-model, electric motor drive sub-model, and ducted fan propulsion sub-model interact through a virtual signal bus link to achieve real-time transmission of simulation parameters between the sub-models.

[0019] Optionally, the instruction parsing computer is equipped with an instruction parsing sub-model. The instruction parsing sub-model is used to parse the joystick's control commands into individual control commands and total power commands for multiple motor simulation modules in the motor drive sub-model. The inputs of the instruction parsing sub-model are the joystick's control commands, the DC bus voltage value output by the DC bus sub-model, and the state of charge simulation feedback parameters output by the battery energy storage sub-model. The outputs of the instruction parsing sub-model include the speed reference values ​​and torque reference values ​​of each motor simulation module.

[0020] Optionally, the method for converting the Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system into C language code and deploying it on a computing board to realize the operation of the digital simulation model of the hybrid electric propulsion system on the computing board includes:

[0021] Perform full-chain compliance checks on the Simulink model, run the model advisor tool to check for and correct issues such as algebraic loops, undefined signals, and module connection logic errors;

[0022] Replace the simulation-only modules in the Simulink model with code generation compatible modules that are compatible with the computing board hardware;

[0023] Based on the hardware architecture of the computing board, all signal data types in the Simulink model are optimized to numerical types that are compatible with the computing board. At the same time, the simulation step size and solver type of the Simulink model are configured to match the real-time computing requirements of the computing board.

[0024] Configure the external interaction interface function and internal logic interface function of the C language code of the digital simulation model of the hybrid electric propulsion system, define the entry function of the C language code of the digital simulation model of the hybrid electric propulsion system, complete the input and output signal mapping, and obtain a standardized code framework;

[0025] Configure the C language code generation parameters according to the hardware characteristics of the computing board, start the automatic code generation function of the MATLAB / Simulink modeling platform to compile the Simulink model, generate intermediate representation files, and map the intermediate representation files into C language code;

[0026] Static analysis is performed on C language code to detect code defects, remove invalid code, and obtain optimized C language code.

[0027] The computing board and the model development computer used to develop the digital simulation model of the hybrid electric propulsion system are connected to communicate. An operating system is installed on the computing board and SSH service is configured. Drivers and dependency libraries are installed on the computing board. The model development computer calls a cross compiler through the generated makefile to compile the optimized C language code into an executable file for the computing board. Then, the executable file and its configuration file are transferred to a specified directory on the computing board via SCP or FTP, so that the program of the digital simulation model of the hybrid electric propulsion system can be run directly on the computing board terminal via command.

[0028] Optionally, the operating information of the hybrid electric propulsion system digital simulation model displayed on the demonstration computer is used to reflect the stability of the hybrid electric propulsion system digital simulation model. The parameters and control strategies of the hybrid electric propulsion system digital simulation model are adjusted according to the stability of the hybrid electric propulsion system digital simulation model until the stability of the hybrid electric propulsion system digital simulation model reaches the preset requirements.

[0029] Optionally, the demonstration computer includes an operating parameter management module, which is used to display the operating parameters of the digital simulation model of the hybrid electric propulsion system. The interface of the operating parameter management module displays the operating parameters of the turboshaft engine, generator, electric motor drive, and battery energy storage.

[0030] Optionally, the demonstration computer includes an energy distribution management module, which is used to demonstrate the energy flow and dynamic distribution logic of the hybrid electric propulsion system digital simulation model under different working modes. The interface of the energy distribution management module presents the energy flow and dynamic distribution logic of the hybrid electric propulsion system under four working modes: pure electric, eddy electric, hybrid charging, and hybrid discharging, through real-time simulation curves, digital instruments, and a visualization structure of the hybrid electric propulsion system.

[0031] Optionally, the demonstration computer includes a flight profile management module. This module simulates the complete flight mission profile of the aircraft and displays real-time flight profiles, real-time monitoring data of flight parameters, and real-time energy distribution data. The interface of the flight profile management module presents the flight altitude-time profile for each flight stage using dynamic curves, and records the energy parameters for each flight stage. The interface also displays aviation instruments for real-time monitoring of flight speed, flight altitude, and pitch angle, reproducing the motion attitude, spatial position, and velocity status of each flight stage. The interface also presents propulsion power, power generation power, and battery power in the form of bar charts and number boxes to dynamically reflect the power coordination of energy distribution in each flight stage.

[0032] In summary, this application includes the following beneficial technical effects:

[0033] This application overcomes the limitations of separating the virtual and real worlds in pure digital simulation testing, achieving real-time closed-loop response from manipulation commands to operating parameters, and making the test scenario closer to the real operating environment; the deep interaction between hardware and simulation model improves the authenticity of control logic and hardware compatibility verification, and reduces the deviation between testing and actual application.

[0034] This application relies on a virtual-real fusion closed loop to simulate various operating conditions, monitor hardware operating parameters in real time, expose potential hardware stability issues in advance, and break through the limitations of traditional single-scenario verification. At the same time, through real-time data interaction, it can visualize energy flow, accurately test and verify the execution effect of system control and energy management strategies under multiple operating conditions, support rapid strategy iteration, and solve the problems of inaccurate and long cycle of traditional verification. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a block diagram of the hardware-in-the-loop test system for the aerospace hybrid electric propulsion system in this application embodiment;

[0037] Figure 2 This is a schematic block diagram of the digital simulation model of the hybrid electric propulsion system in the embodiments of this application;

[0038] Figure 3 This is a flowchart illustrating the deployment of a Simulink model on a computing board in this embodiment of the application;

[0039] Figure 4 This is a block diagram illustrating the principle of the computing board in the embodiments of this application. Detailed Implementation

[0040] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0041] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0042] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0043] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0044] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0045] This application provides a hardware-in-the-loop testing system for an aviation hybrid electric propulsion system.

[0046] like Figure 1 and Figure 2 As shown, a hardware-in-the-loop test system for an aerospace hybrid electric propulsion system includes:

[0047] Hardware platform, including a joystick, an instruction parsing computer, a computing board, and a demonstration computer; a digital simulation model of a hybrid electric propulsion system, including an energy management sub-model, a turboshaft engine sub-model, a generator sub-model, a battery energy storage sub-model, a DC bus sub-model, a motor drive sub-model, and a ducted fan propulsion sub-model. The digital simulation model of the hybrid electric propulsion system runs on the computing board. The Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system is constructed through the MATLAB / Simulink modeling platform. The Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system is converted into C language code and deployed on the computing board to implement the operation of the digital simulation model of the hybrid electric propulsion system on the computing board. Among them, the full English name of MATLAB is Matrix Laboratory, and the Chinese interpretation is matrix laboratory; Simulink is a supporting visualization simulation tool for MATLAB, and the Chinese interpretation is simulation link; MATLAB / Simulink is an integrated technology platform based on the MATLAB programming environment, for dynamic system modeling, simulation, analysis through Simulink, and can generate embedded code.

[0048] Among them, the control instructions generated by the joystick are transmitted to the instruction parsing computer via USB. The instruction parsing computer analyzes the control instructions and sends them to the computing board. The digital simulation model of the hybrid electric propulsion system on the computing board calculates the operating state of the digital simulation model of the hybrid electric propulsion system in real time based on the control instructions and generates operating parameters. The computing board sends the operating parameters to the demonstration computer via UDP communication; the demonstration computer is used to display the operating parameters of the digital simulation model of the hybrid electric propulsion system, to display the energy flow and dynamic distribution logic of the digital simulation model of the hybrid electric propulsion system in different working modes, to simulate the complete flight mission profile of the aircraft and display the real-time flight profile, real-time monitoring data of flight parameters, and real-time energy distribution data. The full English name of USB is Universal Serial Bus, and the Chinese interpretation is universal serial bus; the full English name of UDP is User Datagram Protocol, and the Chinese interpretation is user datagram protocol.

[0049] This application replicates the simulation models of each subsystem of a hybrid electric propulsion system, reproducing the characteristics and interaction logic of each subsystem. It integrates real hardware devices such as joysticks, command parsing computers, high-performance computing boards, and demonstration computers. The joysticks simulate pilot input of control commands, the command parsing computer receives and parses these commands, the high-performance computing boards enable the burning of digital simulation models and real-time computation, and the demonstration computer displays and monitors operational parameters in real time. This establishes a hardware-in-the-loop test platform that simulates the real operating environment of an aviation hybrid electric propulsion system. In a laboratory environment, it comprehensively simulates and tests the operating status of the hybrid electric propulsion system under different flight mission profiles and various complex operating conditions, efficiently verifying the rationality of energy distribution strategies, the effectiveness of complex control logic, and the collaborative matching characteristics between subsystems. Ultimately, it provides comprehensive testing data for the design and optimization of control and energy management strategies for aviation hybrid electric propulsion systems, accelerating the iterative process of aviation hybrid electric propulsion system R&D, significantly reducing the cost and safety risks of actual bench testing, effectively improving the reliability and engineering application capabilities of aviation hybrid electric propulsion systems, and promoting the development of aviation hybrid electric propulsion technology towards practicality and efficiency.

[0050] The specific designs of each sub-model of the digital simulation model of the hybrid electric propulsion system are as follows:

[0051] The energy management sub-model is used to simulate the load demand of the motor drive sub-model, the operating status of the DC bus sub-model, and the state of charge of the battery storage sub-model. It simulates, calculates, and dynamically allocates the output power parameters of the two generator simulation modules in the generator sub-model and the battery simulation module in the battery storage sub-model. The parameter set configured in the energy management sub-model includes power allocation strategy parameters, upper and lower thresholds of the state of charge output by the battery storage sub-model, power supply priority coefficients of the generator sub-model and the battery storage sub-model, and fault redundancy allocation parameters. The inputs of the energy management sub-model are the current parameters of multiple motor simulation modules in the motor drive sub-model and the DC bus voltage value output by the DC bus sub-model. The outputs are the current reference values ​​of the two generator simulation modules in the generator sub-model and the charging and discharging current reference values ​​of the battery simulation module in the battery storage sub-model.

[0052] The turboshaft engine sub-model includes two engine simulation modules. This sub-model responds to simulation control commands from the generator sub-model, outputting corresponding speed parameters through built-in fuel regulation and speed control simulation modules to provide simulated power drive parameters for the generator sub-model. The parameter set configured in the turboshaft engine sub-model includes PID parameters of the speed governors in the two engine simulation modules, fuel flow-speed mapping relationships, and engine maximum speed limit parameters. The inputs to the turboshaft engine sub-model are the speed and torque reference values ​​from the two generator simulation modules in the generator sub-model, and the outputs are the actual speed parameters of the two engine simulation modules in the turboshaft engine sub-model. PID stands for Proportional-Integral-Derivative, and it is a type of controller.

[0053] The generator sub-model includes two generator simulation modules and two rectifier simulation modules, with each module corresponding to an engine simulation module. The generator sub-model is used to simulate the mechanical energy parameters of the turboshaft engine sub-model, converting them into AC simulation parameters. These AC parameters are then converted into DC simulation parameters by the two built-in rectifier simulation modules, providing stable simulated DC power parameters for the DC bus sub-model. The parameter set configured in the generator sub-model includes generator electromagnetic characteristic parameters, stator winding impedance parameters, power factor parameters, generator efficiency curve parameters, rectifier topology parameters, commutation reactance parameters, firing angle control algorithm parameters, generator electromechanical conversion efficiency, and rectifier ripple suppression parameters. The inputs to the generator sub-model are the actual speed parameters of the two engine simulation modules, the speed reference values ​​and torque reference values ​​of the two generator simulation modules within the generator sub-model, and the outputs are the DC-side voltage parameters of the two rectifier simulation modules.

[0054] The battery energy storage sub-model is used to simulate the storage characteristics of electrical energy. It includes a battery simulation module and a conversion simulation module. The conversion simulation module simulates bidirectional power transfer between the battery energy storage sub-model and the DC bus sub-model by simulating a DC / DC converter. The conversion simulation module also responds to charge and discharge commands from the energy management sub-model and simulates voltage stability control of the DC bus sub-model. The parameter set configured in the conversion simulation module includes DC / DC topology parameters, DC / DC conversion efficiency curve parameters, duty cycle control algorithm parameters, battery internal resistance characteristic parameters, and battery charge and discharge rate limit parameters. The inputs to the conversion simulation module are the power reference value, voltage value, and charge / discharge current value of the battery simulation module; the output is the DC-side voltage value of the conversion simulation module. Here, DC stands for Direct Current.

[0055] The DC bus sub-model is used to simulate and integrate the DC simulation electrical parameters output by the two rectifier simulation modules and the simulation electrical parameters output by the converter simulation module, providing unified DC simulation power supply parameters for the motor drive sub-model. The parameter set configured in the DC bus sub-model includes bus equivalent impedance parameters, line loss parameters, and voltage and current sharing control parameters. The inputs of the DC bus sub-model are the current values ​​of multiple motor simulation modules in the motor drive sub-model, the charging and discharging current values ​​of the battery simulation module, the DC output voltage values ​​of the two generator simulation modules, and the output voltage value of the battery simulation module. The outputs are the DC bus voltage value and the DC bus current value.

[0056] The motor drive sub-model includes multiple motor simulation modules. This sub-model receives the simulated power supply signal from the DC bus sub-model, responds to control commands, and outputs simulated mechanical power parameters to drive the ducted fan propulsion sub-model to complete simulated operation. The parameter set configured in the motor drive sub-model includes motor electromagnetic parameters, speed control algorithm parameters, efficiency curve parameters, maximum torque or speed limit parameters, and stator impedance parameters. The inputs to the motor drive sub-model are the DC bus current value, the speed reference value, and the torque reference value of each motor simulation module. The outputs are the actual speed value and actual torque value of each motor simulation module.

[0057] The ducted fan propulsion sub-model is used to convert the simulated mechanical dynamic parameters output by the electric motor drive sub-model into aerodynamic thrust simulation parameters, thereby realizing the simulation reproduction of the aircraft's power output. The parameter set configured in the ducted fan propulsion sub-model includes fan aerodynamic characteristic parameters, blade efficiency parameters, speed-thrust mapping relationship parameters, maximum thrust limit parameters, and aerodynamic loss function parameters. The input of the ducted fan propulsion sub-model is the actual speed value and actual torque value of each electric motor simulation module, and the output is the actual thrust value of the ducted fan propulsion sub-model.

[0058] The energy management sub-model, turboshaft engine sub-model, generator sub-model, battery energy storage sub-model, DC bus sub-model, electric motor drive sub-model, and ducted fan propulsion sub-model interact through a virtual signal bus link to realize the real-time transmission of simulation parameters between the sub-models and form a closed loop of energy flow domain control signals.

[0059] like Figure 3 As shown, the method for converting the Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system into C language code and deploying it on a computing board to realize the operation of the digital simulation model of the hybrid electric propulsion system on the computing board includes:

[0060] Simulink Model Compliance Detection and Error Correction: Perform full-chain compliance detection on the Simulink model, run the model advisor tool to check for and correct algebraic loops, undefined signals, and module connection logic errors;

[0061] Simulink model hardware adaptation and parameter optimization: Replace the modules in the Simulink model that only support simulation with code generation compatible modules that are compatible with the computing board hardware; based on the hardware architecture of the computing board, optimize all signal data types in the Simulink model to numerical types that are compatible with the computing board, reduce memory usage and computation latency, and configure the simulation step size and solver type of the Simulink model to match the real-time computation requirements of the computing board.

[0062] Configure code interface and generation parameters: Configure the external interaction interface function and internal logic interface function of the C language code of the hybrid electric propulsion system digital simulation model, define the entry function of the C language code of the hybrid electric propulsion system digital simulation model, complete the input and output signal mapping, and obtain a standardized code framework; at the same time, enable the code traceability function to make the generated C language code correspond one-to-one with the modules and signal links of the Simulink model, which facilitates subsequent debugging and iteration.

[0063] Generate and optimize C language code: Configure C language code generation parameters according to the hardware characteristics of the computing board, start the automatic code generation function of the MATLAB / Simulink modeling platform to compile the Simulink model, generate intermediate representation files, and map the intermediate representation files to C language code. The C language code includes a main program file, data definition files, interface files, and compilation scripts. The main program file includes the running logic of each sub-model in the digital simulation model of the hybrid electric propulsion system. The data definition files store model parameters and state variables. The interface files declare function prototypes and data structures for hardware driver calls. The compilation scripts contain cross-compilation instructions and link library configurations. Perform static analysis on the C language code to detect code defects such as redundant logic, performance bottlenecks, and syntax errors. Eliminate invalid code, simplify complex calculation logic, and obtain optimized C language code. Optimize the execution efficiency and stability of the code and eliminate potential operational risks of the computing board deployment.

[0064] Configure and deploy the computing board environment: Connect the computing board to the model development computer used to develop the digital simulation model of the hybrid electric propulsion system. Install the operating system and configure SSH service on the computing board. Install drivers and dependency libraries on the computing board. On the model development computer, the generated Makefile calls the cross-compiler to compile the optimized C language code into an executable file for the computing board. Then, transfer the executable file and its accompanying configuration file to a designated directory on the computing board via SCP or FTP to enable direct command execution of the model program on the computing board terminal. The configuration file is a plain text parameter configuration file that accompanies the executable file, including a hardware adaptation configuration file, a model running parameter configuration file, and a communication protocol configuration file. The configuration file is mainly customized during the Simulink model code generation framework configuration stage, and the final product is formed after code optimization, compatibility verification during the cross-compilation stage, and fine-tuning for hardware environment and test conditions before computing board deployment. Among them, SSH stands for Secure Shell; makefile stands for Makefile; SCP stands for Secure Copy Protocol; and FTP stands for File Transfer Protocol.

[0065] This application utilizes modular modeling to break down the system into multiple independent sub-models, decoupling them via a signal bus to improve model maintainability and subsystem reusability, facilitating functional iteration and expansion. Simultaneously, it achieves efficient conversion from MATLAB / Simulink models to C language code through automatic code generation, ensuring consistency between model logic and hardware execution, significantly shortening the cycle from modeling to hardware deployment, and improving R&D efficiency and reliability.

[0066] like Figure 4As shown, the computing board includes two CPU processing nodes, one NPU processing node, a PCIe switching node, and an Ethernet switching node. The two CPU processing nodes and the NPU processing node are interconnected via a PCIe bus. Both CPU processing nodes and the NPU processing node interact with a triple-redundant time-triggered Ethernet network through the PCIe switching node to achieve external data communication. The Ethernet switching node handles the debugging Ethernet switching function for the two CPU processing nodes and the NPU processing node. Considering the need for rapid verification of different NPU platforms in intelligent task deployment and the need for upgrading intelligent computing performance, the NPU processing node is installed as a daughter card on the hardware platform prototype, enabling flexible interchangeability or upgrades with other NPU processing nodes. Each CPU processing node has SPI FLASH storage, DDR4 memory, SSD large-capacity storage, a PCIe 3.0 interface, an Ethernet interface, and a debugging serial port. The NPU processing node has SPI FLASH storage, DDR4 memory, eMMC large-capacity storage, a PCIe 3.0 interface, an Ethernet interface, and a debugging serial port. Among them, CPU stands for Central Processing Unit; NPU stands for Neural Processing Unit; PCIe stands for Peripheral Component Interconnect Express; SPIFLASH stands for Serial Peripheral Interface Flash; DDR4 stands for Double Data Rate 4; SSD stands for Solid State Drive; and eMMC stands for Embedded Multi Media Card.

[0067] The instruction parsing computer is equipped with an instruction parsing sub-model. This sub-model parses the joystick's control commands into individual control commands and total power commands for multiple motor simulation modules in the motor drive sub-model. The inputs to the instruction parsing sub-model are the joystick's control commands, the DC bus voltage value output by the DC bus sub-model, and the state-of-charge simulation feedback parameters output by the battery storage sub-model. The outputs of the instruction parsing sub-model include the speed reference values ​​and torque reference values ​​for each motor simulation module. The parameter set configured in the instruction parsing sub-model includes instruction parsing algorithm parameters, power allocation coefficients for each motor simulation module in the motor drive sub-model, flight mode mapping matrix, upper and lower voltage limit parameters for the DC bus sub-model, and constraint thresholds such as the charge safety range output by the battery storage sub-model.

[0068] The operating information of the hybrid electric propulsion system digital simulation model displayed on the demonstration computer is used to reflect the stability of the hybrid electric propulsion system digital simulation model. The parameters and control strategies of the hybrid electric propulsion system digital simulation model are adjusted according to the stability of the hybrid electric propulsion system digital simulation model until the stability of the hybrid electric propulsion system digital simulation model reaches the preset requirements.

[0069] In this embodiment, data corresponding to various test scenarios are pre-stored in the computing board. The demonstration computer selects the corresponding test command, and the computing board inputs the corresponding data into the hybrid electric propulsion system digital simulation model. The hybrid electric propulsion system digital simulation model runs the corresponding parameters to simulate the corresponding flight scenario. Specifically, a multi-dimensional test scenario library covering various flight profiles is constructed. Test scenarios are selected on the demonstration computer, such as extreme environments like high temperature and low air pressure, degradation conditions like battery capacity decay and generator efficiency fluctuations, and sudden failures. The corresponding data in the scenario library is input into the hybrid electric propulsion system digital simulation model. The energy management sub-model dynamically adjusts the management strategy parameters according to the preset logic. The demonstration computer collects the response data of each subsystem in real time and then visualizes it in the form of energy flow graphs, parameter fluctuation curves, etc., to comprehensively verify the adaptability of the strategy in complex scenarios, the fault tolerance of the control logic, and the collaborative ability of each sub-model.

[0070] By inputting simulated pilot commands via a joystick, typical flight conditions are simulated. The model's operation on the computational board is observed through a demonstration computer to verify its correct response and the normal fluctuation of key parameters, such as propulsion power following command changes and reasonable fluctuations in the state of charge output of the battery energy storage sub-model, ensuring that the model's dynamic characteristics meet design expectations. Extreme conditions, such as sudden load changes and subsystem failures, are recorded to assess system stability. If deviations are found, the system returns to the Simulink model to adjust parameters or control strategies until the stability of the hybrid electric propulsion system digital simulation model reaches the preset requirements.

[0071] The specific design of the demonstration computer is as follows:

[0072] The demonstration computer includes an operating parameter management module, which displays the operating parameters of the digital simulation model of the hybrid electric propulsion system. The module's interface displays the operating parameters of the turboshaft engine, generator, electric motor drive, and battery energy storage. Specifically, a cross-sectional schematic diagram of the turboshaft engine visually presents the internal turbine and compressor structure. Instruments such as shaft power, fuel consumption per unit power, and high and low pressure turbine speeds are used to monitor power output, fuel efficiency, and speed matching in real time. Simultaneously, contour curves of fuel consumption per unit power and turbine characteristic curves are used to analyze performance patterns under different operating conditions. Combined with schematic diagrams of the generator stator and rotor structure, speed, output power, and bus voltage instruments provide feedback on speed, power generation, and voltage stability. An overspeed indicator simulates fault warning and safety protection functions. When the generator speed exceeds a preset safety threshold, detected by speed sensors and frequency detection, the overspeed indicator triggers, simultaneously activating protection devices to stop the unit in time. A torque-speed-efficiency contour plot quantitatively displays the efficiency distribution under multiple parameters, quickly locating the high-efficiency operating range. The diagram showcases the electric motor's structure, displaying instruments such as motor speed, output power, and bus voltage reflecting power output and voltage status. Output power characteristic curves illustrate power and efficiency variations across the entire speed range, supporting the propulsion system's power matching design. An overspeed indicator light for the motor is also included. A battery operating principle diagram illustrates the battery's internal working mechanism, dynamically providing energy status feedback through charging, discharging, and standby indicator lights. Battery state-of-charge displays and current and power curves monitor real-time battery pack status changes, accurately characterizing battery features and providing a basis for optimizing battery management strategies.

[0073] The demonstration computer includes an energy distribution management module, which displays the energy flow and dynamic distribution logic of the hybrid electric propulsion system's digital simulation model under different operating modes. The module's interface presents the energy flow and dynamic distribution logic of the hybrid electric propulsion system under four operating modes: pure electric, eddy electric, hybrid charging, and hybrid discharging, through real-time simulation curves, digital instruments, and a visualized structure of the hybrid electric propulsion system. Specifically, in pure electric mode: the turboshaft engine and generator are not operating, and energy is solely supplied by the high-voltage battery pack. The electrical energy stored in the battery is directionally distributed to all electrical loads via the DC bus. At this time, energy flows unidirectionally from battery to DC bus to multiple loads. The battery state-of-charge curve in the interface continuously decreases during the discharge process, intuitively reflecting the energy consumption pattern. In eddy electric mode: the turboshaft engine starts and drives the generator, converting the mechanical energy of the turboshaft engine into electrical energy. Electrical energy is distributed via the DC bus, with the energy flow path being turboshaft engine → generator → DC bus → load. The turboshaft engine power curve in the interface increases with the rotational speed, synchronously mapping the conversion process from mechanical energy to electrical energy. Hybrid Charging Mode: This mode focuses on simultaneously meeting energy storage and load demands on the power generation side. The turboshaft engine and generator serve as the main energy sources. Their output power is shunted via the DC bus, simultaneously charging the battery and supplying power to the propulsion load. The bus voltage remains stable at its rated value, and power balance on both sides is monitored in real time to avoid conflicts between charging and load power supply. Energy follows a bidirectional shunting path: generator → DC bus → battery + propulsion load, enabling coordinated charging and low-power propulsion. Hybrid Discharge Mode: This mode is the core scenario for dual-energy synergistic energy release. The generator and high-voltage battery pack act as a hybrid energy source, with the energy management controller dynamically allocating output power according to load demand. The interface clearly presents the hybrid energy release closed loop of generator + battery → DC bus → load, intuitively reflecting the precise control of dual-source output by the energy management strategy.

[0074] The demonstration computer includes a flight profile management module, which simulates the complete flight mission profile of the aircraft and displays real-time flight profiles, real-time monitoring data of flight parameters, and real-time energy distribution data. The interface of the flight profile management module presents the flight altitude-time profile for each flight stage as a dynamic curve, and records key energy parameters for each flight stage. The interface of the flight profile management module also displays aviation instruments for real-time monitoring of flight speed, flight altitude, and pitch angle, accurately reproducing the motion attitude, spatial position, and velocity status of each flight stage. The interface of the flight profile management module also presents propulsion power, power generation power, and battery power in the form of bar charts and number boxes to dynamically reflect the power coordination of energy distribution in each flight stage.

[0075] The demonstration computer in this application constructs a digital closed-loop simulation environment through the visualization of flight profiles, real-time monitoring of flight parameters, and power linkage of the energy system. It can cover the entire flight phase, including takeoff, cruise, and landing, and provides an intuitive and high-precision analysis tool for verifying energy distribution strategies under different profiles and optimizing the matching of electric propulsion systems with flight conditions.

[0076] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A hardware-in-the-loop test system for an aerospace hybrid electric propulsion system, characterized in that, include: The hardware platform includes a joystick, an instruction parsing computer, computing boards, and a demonstration computer; The digital simulation model of the hybrid electric propulsion system includes an energy management sub-model, a turboshaft engine sub-model, a generator sub-model, a battery energy storage sub-model, a DC bus sub-model, an electric motor drive sub-model, and a ducted fan propulsion sub-model. The digital simulation model of the hybrid electric propulsion system runs on the computing board. The Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system is constructed through the MATLAB / Simulink modeling platform. The Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system is converted into C language code and deployed on the computing board to realize the operation of the digital simulation model of the hybrid electric propulsion system on the computing board. The control commands generated by the joystick are transmitted to the command parsing computer via USB. The command parsing computer parses the control commands and sends them to the computing board. The hybrid electric propulsion system digital simulation model on the computing board calculates the operating status of the hybrid electric propulsion system digital simulation model in real time based on the control commands and generates operating parameters. The computing board sends the operating parameters to the demonstration computer via UDP communication. The demonstration computer is used to display the operating parameters of the digital simulation model of the hybrid electric propulsion system, to display the energy flow and dynamic distribution logic of the digital simulation model of the hybrid electric propulsion system under different working modes, and to simulate the complete flight mission profile of the aircraft and display the real-time flight profile, real-time monitoring data of flight parameters, and real-time energy distribution data. The turboshaft engine sub-model is used to respond to the simulation control commands of the generator sub-model. It outputs corresponding speed parameters through the built-in fuel regulation simulation module and speed regulation simulation module to provide simulation power drive parameters for the generator sub-model. The parameter set configured in the turboshaft engine sub-model includes the PID parameters of the engine governor, the fuel flow-speed mapping relationship, and the engine maximum speed limit parameters. The generator sub-model is used to simulate the mechanical energy parameters of the turboshaft engine sub-model, which are then converted into AC simulation parameters and then into DC simulation parameters via the built-in rectifier simulation module. This provides stable simulated DC power parameters for the DC bus sub-model. The parameter set configured in the generator sub-model includes generator electromagnetic characteristic parameters, stator winding impedance parameters, power factor parameters, generator efficiency curve parameters, rectifier topology parameters, commutation reactance parameters, firing angle control algorithm parameters, generator electromechanical conversion efficiency, and rectifier ripple suppression parameters. The ducted fan propulsion sub-model is used to convert the simulated mechanical dynamic parameters output by the electric motor drive sub-model into aerodynamic thrust simulation parameters, thereby realizing the simulation reproduction of the aircraft's power output. The parameter set configured in the ducted fan propulsion sub-model includes fan aerodynamic characteristic parameters, blade efficiency parameters, speed-thrust mapping relationship parameters, maximum thrust limit parameters, and aerodynamic loss function parameters.

2. The hardware-in-the-loop test system for an aerospace hybrid electric propulsion system according to claim 1, characterized in that, The computing board includes two CPU processing nodes and one NPU processing node. The two CPU processing nodes and the NPU processing node are interconnected via a PCIe bus. Both CPU processing nodes and the NPU processing node communicate with each other via triple-redundancy time-triggered Ethernet.

3. The hardware-in-the-loop test system for an aerospace hybrid electric propulsion system according to claim 1, characterized in that, The energy management sub-model is used to perform simulation calculations and dynamically allocate the output power parameters of the two generator simulation modules in the generator sub-model and the battery simulation module in the battery energy storage sub-model based on the simulated load demand of the motor drive sub-model, the simulated operating state of the DC bus sub-model, and the simulated state of charge of the battery energy storage sub-model. The parameter set configured by the energy management sub-model includes power allocation strategy parameters, upper and lower limit thresholds of the battery state of charge output by the battery energy storage sub-model, energy supply priority coefficients of the generator sub-model and the battery energy storage sub-model, and fault redundancy allocation parameters. The battery energy storage sub-model is used to simulate the storage characteristics of stored electrical energy. The battery energy storage sub-model has a built-in conversion simulation module. The conversion simulation module realizes bidirectional simulated power transfer between the battery energy storage sub-model and the DC bus sub-model by simulating a DC / DC converter. The conversion simulation module is also used to respond to the charging and discharging commands of the energy management sub-model and to simulate the voltage stability control of the DC bus sub-model. The parameter set configured by the conversion simulation module includes DC / DC topology parameters, DC / DC conversion efficiency curve parameters, duty cycle control algorithm parameters, battery internal resistance characteristic parameters, and battery charging and discharging rate limit parameters. The DC bus sub-model is used to simulate and integrate the DC simulation electrical parameters output by the rectifier simulation module and the simulation electrical parameters output by the converter simulation module, providing unified DC simulation power supply parameters for the motor drive sub-model. The parameter set configured in the DC bus sub-model includes bus equivalent impedance parameters, line loss parameters, and voltage and current sharing control parameters. The motor drive sub-model is used to receive the simulation power supply signal of the DC bus sub-model, respond to the operation command and output the simulation mechanical power parameters, and drive the ducted fan propulsion sub-model to complete the simulation operation. The parameter set configured by the motor drive sub-model includes motor electromagnetic parameters, speed control algorithm parameters, efficiency curve parameters, maximum torque or speed limit parameters and stator impedance parameters. The energy management sub-model, turboshaft engine sub-model, generator sub-model, battery energy storage sub-model, DC bus sub-model, electric motor drive sub-model, and ducted fan propulsion sub-model interact through a virtual signal bus link to achieve real-time transmission of simulation parameters between the sub-models.

4. The hardware-in-the-loop test system for an aerospace hybrid electric propulsion system according to claim 3, characterized in that, The instruction parsing computer is equipped with an instruction parsing sub-model. The instruction parsing sub-model is used to parse the joystick's control commands into individual control commands and total power commands for multiple motor simulation modules in the motor drive sub-model. The inputs of the instruction parsing sub-model are the joystick's control commands, the DC bus voltage value output by the DC bus sub-model, and the state of charge simulation feedback parameters output by the battery energy storage sub-model. The outputs of the instruction parsing sub-model include the speed reference values ​​and torque reference values ​​of each motor simulation module.

5. The hardware-in-the-loop test system for an aerospace hybrid electric propulsion system according to claim 1, characterized in that, The method for converting the Simulink model corresponding to the digital simulation model of the hybrid electric propulsion system into C language code and deploying it on a computing board to enable the running of the digital simulation model of the hybrid electric propulsion system on the computing board includes: Perform end-to-end compliance checks on the Simulink model, run the model advisor tool to identify and correct issues such as algebraic loops, undefined signals, and module connection logic errors; Replace the Simulink model with a simulation-only module that is compatible with the computing board hardware by generating a code-compatible module. Based on the hardware architecture of the computing board, all signal data types in the Simulink model are optimized to numerical types that are compatible with the computing board. At the same time, the simulation step size and solver type of the Simulink model are configured to match the real-time computing requirements of the computing board. Configure the external interaction interface function and internal logic interface function of the C language code of the digital simulation model of the hybrid electric propulsion system, define the entry function of the C language code of the digital simulation model of the hybrid electric propulsion system, complete the input and output signal mapping, and obtain a standardized code framework; Configure the C language code generation parameters according to the hardware characteristics of the computing board, start the automatic code generation function of the MATLAB / Simulink modeling platform to compile the Simulink model, generate intermediate representation files, and map the intermediate representation files into C language code; Static analysis is performed on C language code to detect code defects, remove invalid code, and obtain optimized C language code. The computing board and the model development computer used to develop the digital simulation model of the hybrid electric propulsion system are connected to communicate. An operating system is installed on the computing board and SSH service is configured. Drivers and dependency libraries are installed on the computing board. The model development computer calls a cross compiler through the generated makefile to compile the optimized C language code into an executable file for the computing board. Then, the executable file and its configuration file are transferred to a specified directory on the computing board via SCP or FTP, so that the program of the digital simulation model of the hybrid electric propulsion system can be run directly on the computing board terminal via command.

6. The hardware-in-the-loop test system for an aerospace hybrid electric propulsion system according to claim 1, characterized in that, The operating information of the hybrid electric propulsion system digital simulation model displayed on the demonstration computer is used to reflect the stability of the hybrid electric propulsion system digital simulation model. The parameters and control strategies of the hybrid electric propulsion system digital simulation model are adjusted according to the stability of the hybrid electric propulsion system digital simulation model until the stability of the hybrid electric propulsion system digital simulation model reaches the preset requirements.

7. The hardware-in-the-loop test system for an aerospace hybrid electric propulsion system according to claim 1, characterized in that, The demonstration computer includes an operating parameter management module, which is used to display the operating parameters of the digital simulation model of the hybrid electric propulsion system. The interface of the operating parameter management module displays the operating parameters of the turboshaft engine, generator, electric motor drive, and battery energy storage.

8. The hardware-in-the-loop test system for an aerospace hybrid electric propulsion system according to claim 1, characterized in that, The demonstration computer includes an energy distribution management module, which is used to display the energy flow and dynamic distribution logic of the hybrid electric propulsion system digital simulation model under different working modes. The interface of the energy distribution management module presents the energy flow and dynamic distribution logic of the hybrid electric propulsion system under four working modes: pure electric, eddy electric, hybrid charging, and hybrid discharging, through real-time simulation curves, digital instruments, and a visualization structure of the hybrid electric propulsion system.

9. The hardware-in-the-loop test system for an aerospace hybrid electric propulsion system according to claim 1, characterized in that, The demonstration computer includes a flight profile management module, which simulates the complete flight mission profile of the aircraft and displays real-time flight profiles, real-time monitoring data of flight parameters, and real-time energy distribution data. The interface of the flight profile management module presents the flight altitude-time profile for each flight stage as a dynamic curve, and records the energy parameters for each flight stage. The interface of the flight profile management module also displays aviation instruments for real-time monitoring of flight speed, flight altitude, and pitch angle, reproducing the motion attitude, spatial position, and velocity status of each flight stage. The interface of the flight profile management module also presents propulsion power, power generation power, and battery power in the form of bar charts and number boxes to dynamically reflect the power coordination of energy distribution in each flight stage.

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