Simulation method and device of hybrid electric propulsion system, electronic equipment and storage medium

Abstract

The application discloses a simulation method and device of a hybrid electric propulsion system, electronic equipment and a storage medium. The method comprises the following steps: S1, establishing a component-level full-state dynamic model of a turbo-shaft engine to obtain an engine model; S2, establishing a generator model, a motor model, a power battery model and a propeller model; S3, designing a full-state control law of the hybrid electric propulsion system, including an engine full-state control law, a generator control law and a motor control law; S4, designing a full-working-condition energy management strategy considering dynamic response capability; and S5, integrating multi-disciplinary models and carrying out joint simulation verification. The simulation method of the hybrid electric propulsion system realizes multi-disciplinary response full-state modeling, full-coverage comprehensive control and energy management constraint simulation of the hybrid electric propulsion system under a unified simulation architecture, and can realize four energy management working modes of a turbo-electric mode, a hybrid-electric mode, a pure-electric mode and a charging mode.

Description

Technical Field

[0001] This application relates to the field of power communication technology, and in particular to simulation methods, apparatus, electronic devices and storage media for hybrid electric propulsion systems. Background Technology

[0002] With the global aviation industry's urgent need for low-carbon emissions, high-efficiency, and low-noise power systems, electrification has become a major transformative direction in aviation technology, following gas turbine engines. For aircraft with increasingly demanding requirements for large payloads and long ranges, such as 100-seat electric aircraft and medium-to-large eVTOLs, turbine-based hybrid electric propulsion systems, composed of high-efficiency gas turbine engines, high power-to-weight ratio generators and motors, large-capacity, high-energy-density power batteries, and lightweight, high-efficiency thrusters, are becoming an important direction for the future development of aviation hybrid electric propulsion technology. However, such systems involve deep cross-coupling of multiple disciplines, including aerodynamics, thermodynamics, mechanical dynamics, electrodynamics, electrochemistry, and aerodynamics, and the dynamic response time scales of various components differ greatly (engines have second-level response, while motors and batteries have millisecond-level response), making full-condition modeling, multi-energy coordinated control, and energy management extremely complex. Using system-level models that can reflect the coordinated matching and dynamic coupling characteristics of multiple disciplines has become a core technology in the design of aviation hybrid electric propulsion systems both domestically and internationally.

[0003] Currently, modeling and simulation research on hybrid electric propulsion systems, both domestically and internationally, can be mainly categorized into the following types, among which the existing technical solutions most similar to this application mainly include: (1) System-level simulation scheme based on simplified dynamic models. Taking Rolls-Royce North America's Distributed Turbine-Powered Propulsion (TeDP) system for the 300-seat blended wing-body future aircraft N3-X as an example, this scheme establishes a simplified engine model that only reflects the dynamic relationship of power parameters. Inertial and saturated elements are used to establish dynamic models of the generator, inverter, and propulsion. These simplified dynamic models are used to study the stability, transient response, control laws, and safety of the high-voltage power grid of the eddy electric propulsion aircraft. The advantages of this scheme are its simple model and high computational efficiency, but its disadvantage is that it does not retain enough of the disciplinary characteristics of each component.

[0004] (2) A scheme based on discrete modeling and co-simulation using specialized tools. Taking the hybrid electric propulsion system of the 150-seat STARC-ABL single-channel turbine generator demonstrator with boundary layer removal by NASA's Green Research Center as an example, this scheme utilizes the Digital Propulsion System Simulation Model (NPSS) to establish dynamic models of the geared turbofan engine and the electric rear fan. Simultaneously, it uses the MATLAB / SimPowerSystems toolkit to establish electrical and mechanical dynamic models of equipment such as AC / DC converters, PWM inverters, and permanent magnet motors. These models are then integrated into NASA's Electric Aircraft Test Bench (NEAT) to simulate the dynamic characteristics of the engine rotor and the information interaction between subsystems. This scheme represents the mainstream technical route for multidisciplinary co-simulation of hybrid electric propulsion systems, where each discipline uses its familiar specialized tools to establish a professional model, and then performs co-simulation through an integrated platform.

[0005] (3) Steady-state / quasi-steady-state simulation scheme based on component-level thermodynamic models. Represented by the work conducted by NASA's Green Research Center in the Revolutionary Vertical Takeoff and Landing Technology (RVLT) program, this scheme utilizes NPSS and gas turbine engine weight analysis software (WATE++) to establish thermodynamic and weight models of turboshaft engines with various power ranges (large, medium, and small) and single and dual rotor configurations. It primarily outputs steady-state performance parameters such as shaft power range, serving as a common benchmark for current and future work. This scheme is mainly applicable to the engine selection and preliminary design stages, and its ability to characterize dynamic processes and multidisciplinary coupling is limited.

[0006] Based on the above-mentioned prior art solutions most similar to this application, they have the following main drawbacks and shortcomings: (1) Lack of a unified and easily implemented multidisciplinary joint simulation architecture. In the existing technology, the models of various disciplines (such as the engine model in NPSS and the electrical model in SimPowerSystems) usually run on different platforms and need to be combined through a customized integration environment (such as NEAT). The system is complex, the interface standards are not unified, and the interdisciplinary ability of researchers is required. It is difficult to build and iterate quickly under normal engineering research and development conditions.

[0007] (2) The problem of equivalent coordination of dynamic response of multi-disciplinary models has not been solved. In the existing technology, the second-level dynamic response of the turboshaft engine is directly coupled with the millisecond-level electrical dynamic response of the generator and motor, and there is a lack of a method to reasonably allocate the equivalent level of dynamic response of each component model. Either the engine model is too simplified and cannot reflect the real power change limit; or the electrical model is too detailed, resulting in too small simulation step size and low computational efficiency, making it difficult to take into account the needs of system-level control and energy management design and the preservation of the technical characteristics of each discipline.

[0008] (3) Lack of control laws covering all operating conditions of hybrid electric propulsion systems. Existing technologies mostly focus on the control of steady-state cruise conditions or specific operating modes (such as power generation mode), lacking a set of control laws that can cover the entire process of turboshaft engine from ground start-up, ground slow / air slow switching, load increase / decrease to shutdown. At the same time, the control of electrical equipment such as generators, motors, and power batteries has not formed a complete coordinated control logic with the engine, making it difficult for existing models to drive the system to complete dynamic simulation from standstill to all operating conditions.

[0009] (4) The constraints of the dynamic response capability of the generator system on the energy management strategy have not been fully considered. The existing energy management strategies are mainly based on steady-state power balance or simple peak shaving and valley filling rules, and have not designed corresponding constraints for the limited power loading / unloading rate capability of the series turboshaft generator system. When the propeller power demand changes rapidly, the engine power turbine speed is prone to large fluctuations, which may even lead to generator loss of synchronism or engine shutdown, affecting the stability and safety of the system. Summary of the Invention

[0010] This application provides a simulation method for hybrid electric propulsion systems, addressing the technical problems of existing technologies, such as the lack of a unified simulation architecture, equivalent synergy of multidisciplinary responses, full coverage of control laws, and constraints on energy management strategies.

[0011] This application is achieved through the following solution: The simulation method for hybrid electric propulsion systems includes the following steps: S1. Establish a component-level full-state dynamic model of the turboshaft engine to obtain the engine model. This includes using the full-state component method, based on the cavity dynamics equation, rotor dynamics equation and variable specific heat calculation method, to establish a nonlinear differential equation model that can reflect the entire process of the engine from static start-up, load increase / decrease to shutdown in the selected main simulation platform. S2. Establish generator model, motor model, power battery model and propeller model, including in the selected sub-simulation platform, establish the average characteristic model of megawatt-level permanent magnet synchronous generator and motor based on average electrical characteristics and steady-state mechanical characteristics, establish the dynamic equivalent circuit model of power battery, and establish the aerodynamic model of variable pitch thrust propeller and fixed pitch lift propeller based on dimensionless characteristics. S3. Design the full-state control law of the hybrid electric propulsion system, including the full-state control law of the engine, the control law of the generator and the control law of the electric motor. The full-state control law of the engine includes the ground start control law of the engine, the ground idle control law, the ground idle / air idle conversion control law, the load increase / decrease control law, the shutdown control law, and the limitation and protection control logic. S4. Design a full-condition energy management strategy that considers dynamic response capability, including setting power distribution rules for four working modes: eddy electric hybrid mode, series hybrid mode, pure electric mode, and charging hybrid mode, based on the maximum loading rate and minimum unloading rate of the generator system, to achieve coordinated power distribution between the generator and the power battery. S5. Integrate multidisciplinary models and conduct joint simulation verification, including integrating the engine model with the generator model, electric motor model, power battery model and propeller model through the simulation joint simulation interface, setting simulation working condition sequence, running simulation and comparing the test data of each component with the prototype to verify the accuracy of the model and the effectiveness of the control strategy.

[0012] Another aspect of this application provides a simulation apparatus for a hybrid electric propulsion system, including: The main model building module is used to build a component-level full-state dynamic model of the turboshaft engine to obtain the engine model. This includes using the full-state component method, based on the cavity dynamics equation, rotor dynamics equation and variable specific heat calculation method, to build a nonlinear differential equation model that can reflect the entire process of the engine from static start-up, load increase / decrease to shutdown in the selected main simulation platform. The sub-model building module is used to build generator models, motor models, power battery models and propeller models. It includes building average characteristic models of megawatt-level permanent magnet synchronous generators and motors based on average electrical characteristics and steady-state mechanical characteristics in the selected sub-simulation platform, building dynamic equivalent circuit models of power batteries, and building aerodynamic models of variable-pitch thrust propellers and fixed-pitch lift propellers based on dimensionless characteristics. The full-state control law construction module is used to design the full-state control laws of the hybrid electric propulsion system, including the engine full-state control laws, generator control laws, and electric motor control laws. The engine full-state control laws include the engine ground start control law, ground idle control law, ground idle / air idle conversion control law, load increase / decrease control law, shutdown control law, and limit protection control logic. The full-condition energy management strategy construction module is used to design a full-condition energy management strategy that takes into account dynamic response capabilities. This includes setting power allocation rules for four working modes—eddy electric hybrid mode, series hybrid mode, pure electric mode, and charging hybrid mode—based on the maximum loading rate and minimum unloading rate of the generator system, so as to realize coordinated power allocation between the generator and the power battery. The model integration and co-simulation verification module is used to integrate multi-disciplinary models and conduct co-simulation verification. This includes integrating the engine model with the generator model, electric motor model, power battery model and propeller model through the simulation co-simulation interface, setting simulation working condition sequences, running simulations and comparing the test data of each component with the prototype to verify the accuracy of the model and the effectiveness of the control strategy.

[0013] This application also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the simulation method of the hybrid electric propulsion system.

[0014] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the simulation method for the hybrid electric propulsion system.

[0015] This application also provides a computer program product, including a computer program or computer-executable instructions, which, when executed by a processor, implement the simulation method of the hybrid electric propulsion system.

[0016] Compared with the prior art, this application can produce the following beneficial effects: (1) In terms of multidisciplinary co-simulation architecture, it is more feasible and convenient for engineering implementation. In the existing technology, engine models usually run in dedicated tools such as NPSS, and electrical models run in SimPowerSystems. They require the use of complex integration environments (such as NEAT) to achieve co-simulation, resulting in complex systems and inconsistent interface standards. This application adopts a main model plus sub-model architecture, and realizes data interaction through mature co-simulation interfaces. There is no need to develop additional customized integration platforms, which greatly reduces the difficulty of implementing multidisciplinary co-simulation and facilitates rapid construction and iteration under normal engineering research and development conditions.

[0017] (2) In terms of the equivalent synergy of dynamic response of multidisciplinary models, both simulation accuracy and computational efficiency are taken into account.

[0018] In existing technologies, either the engine model is overly simplified (e.g., using an inertial element instead), failing to realistically reflect the dynamic characteristics such as speed and temperature during power changes; or the electrical model is overly detailed (e.g., a PWM transient model above 10kHz), resulting in excessively small simulation steps and low computational efficiency. This application proposes a dynamic response equivalent synergistic method: the engine retains complete rotor and cavity dynamics (realistic response at the second level), the electrical model adopts average characteristics and introduces a torque limit line (equivalent to the hundreds of millisecond level), and the battery model retains dynamics at the tens of seconds level. This method satisfies the accuracy requirements of system-level control and energy management design, maximizes the preservation of the technical characteristics of each discipline, and significantly improves simulation efficiency.

[0019] (3) Regarding the full-state control law, it achieves full-condition coverage from start-up to shutdown. Existing technologies mostly focus on simple control laws for steady-state cruise conditions or specific operating modes, lacking complete control logic for the entire process of engine ground start-up, ground slow / air slow switching, load feedforward, limit protection, and shutdown. This application designs a control law covering the entire state of the turboshaft engine and forms a complete collaborative system with the control laws of the generator and electric motor, realizing the driving and control of the entire process and state of the hybrid electric propulsion system from start-up from standstill, load feedforward, to shutdown, filling the gap in the existing technology for non-steady-state control.

[0020] (4) Regarding the energy management strategy, the constraints of the dynamic capability of the generator system are considered. Existing energy management strategies are mainly based on steady-state power balance and do not consider the limited power loading / unloading rate capability of the series-connected turboshaft generator system. When the propeller power changes rapidly, it can easily lead to large fluctuations in engine speed or even shutdown. This application is the first to embed the maximum loading rate and minimum unloading rate of the generator system as constraints into the energy management strategy, limiting the generator power change rate to within the range of the engine's dynamic response capability, with the excess being borne by the power battery. This strategy effectively suppresses the fluctuation of the power turbine speed (simulation shows that the overshoot is less than 3%), significantly improving the dynamic stability and safety of the system.

[0021] (5) Regarding model verification, thorough experimental data comparison and verification were conducted. Unlike many existing studies that only focus on digital simulation, this application compared and verified the mathematical models of the turboshaft engine, generator, lift electric propulsion subsystem, and thrust electric propulsion subsystem with experimental data from a megawatt-level hybrid electric propulsion prototype experimental platform. The results show that the maximum steady-state deviation of the engine does not exceed 2%, the average relative error of the generator is 0.39% and the steady-state deviation is less than 5%, the power deviation of the lift motor is less than 4%, the thrust and torque deviation of the lift propeller are less than 3%, and the simulation data of the thrust motor and thrust propeller are consistent with the design data. The thorough experimental verification ensures the engineering credibility of the model and method established in this application.

[0022] In addition to the purposes, features, and advantages described above, this application has other purposes, features, and advantages. These will be further described in detail below with reference to figures. Attached Figure Description

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0024] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein: Figure 1 This is a flowchart illustrating the simulation method of a hybrid electric propulsion system according to a preferred embodiment of this application; Figure 2 This is a schematic diagram of the composition of the turboshaft-based hybrid electric propulsion system of this application; Figure 3 This is a schematic diagram of the rotational speed command values ​​of the lift propeller and thrust propeller according to a preferred embodiment of this application; Figure 4 This is a schematic diagram of the thrust propeller pitch variation according to a preferred embodiment of this application; Figure 5 This is the variation of engine gas turbine and power turbine speeds in the preferred embodiment of this application under eddy electric hybrid mode; Figure 6 This is a schematic diagram of the change in the state of charge of the power battery in the eddy electric hybrid mode according to a preferred embodiment of this application; Figure 7 This application's preferred embodiment describes the speed changes of the engine's gas turbine and power turbine in pure electric mode. Figure 8 This is a schematic diagram of the change in the state of charge of the power battery in pure electric mode according to a preferred embodiment of this application; Figure 9 This is the variation of engine gas turbine speed in the preferred embodiment of this application under series hybrid mode; Figure 10 This is a schematic diagram of the change in the state of charge of the power battery in the series hybrid mode according to a preferred embodiment of this application; Figure 11 This is a schematic diagram of the engine gas turbine speed change in the preferred embodiment of this application under the charging hybrid mode; Figure 12 This is a schematic diagram of the change in the state of charge of the power battery in the charging hybrid mode according to a preferred embodiment of this application; Figure 13 This is a schematic diagram of the module of a simulation device for a hybrid electric propulsion system according to a preferred embodiment of this application; Figure 14 This is a schematic block diagram of an electronic device according to a preferred embodiment of this application; Figure 15 This is a schematic diagram of the internal structure of a computer device according to a preferred embodiment of this application. Detailed Implementation

[0025] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0026] It should be noted that the execution subject of this embodiment can be a computing service system with data processing, network communication and program running functions, such as a tablet computer, personal computer, mobile phone, etc., or a simulation device of a hybrid electric propulsion system that can realize the above functions. The following uses a simulation device of a hybrid electric propulsion system as the execution subject to describe this embodiment and the following embodiments.

[0027] like Figure 1 As shown, a preferred embodiment of this application provides a simulation method for a hybrid electric propulsion system, comprising the following steps: S1. Establish a component-level full-state dynamic model of the dual-shaft free turbine turboshaft engine to obtain the engine model. This includes using the full-state component method, based on the cavity dynamics equation, rotor dynamics equation and variable specific heat calculation method, to establish a nonlinear differential equation model that can reflect the entire process of the engine from static start-up, load increase / decrease to shutdown in the selected main simulation platform. S2. Establish generator model, motor model, power battery model and propeller model, including in the selected sub-simulation platform, establish the average characteristic model of megawatt-level permanent magnet synchronous generator and motor based on average electrical characteristics and steady-state mechanical characteristics, establish the dynamic equivalent circuit model of power battery, and establish the aerodynamic model of variable pitch thrust propeller and fixed pitch lift propeller based on dimensionless characteristics. S3. Design the full-state control law of the hybrid electric propulsion system, including the full-state control law of the engine, the control law of the generator and the control law of the electric motor. The full-state control law of the engine includes the ground start control law of the engine, the ground idle control law, the ground idle / air idle conversion control law, the load increase / decrease control law, the shutdown control law, and the limitation and protection control logic. S4. Design a full-condition energy management strategy that considers dynamic response capability, including setting power distribution rules for four working modes: eddy electric hybrid mode, series hybrid mode, pure electric mode, and charging hybrid mode, based on the maximum loading rate and minimum unloading rate of the generator system, to achieve coordinated power distribution between the generator and the power battery. S5. Integrate multidisciplinary models and conduct joint simulation verification, including integrating the engine model with the generator model, electric motor model, power battery model and propeller model through the simulation joint simulation interface, setting simulation working condition sequence, running simulation and comparing the test data of each component with the prototype to verify the accuracy of the model and the effectiveness of the control strategy.

[0028] This embodiment proposes a simulation method for hybrid electric propulsion systems, specifically a multidisciplinary full-state modeling, integrated control, and energy management simulation method for a megawatt-class series-connected turboshaft-based hybrid electric propulsion system. For example... Figure 2 As shown, the hybrid electric propulsion system mainly consists of a free-turbo dual-shaft turboshaft engine, a megawatt-class permanent magnet synchronous generator, a high-energy-density power battery, multiple lift motors and lift propellers, thrust motors and thrust propellers, etc., and can realize four energy management working modes: vortex-electric mode, hybrid electric mode, pure electric mode and charging mode.

[0029] In a preferred embodiment of this application, when the engine model is obtained by establishing the component-level full-state dynamic model of the turboshaft engine in step S1, the engine model obtained by establishing the component-level full-state dynamic model of the turboshaft engine in the MATLAB / Simulink platform is used as the main model of the entire hybrid electric propulsion system, which is responsible for providing the aerodynamic, thermodynamic and mechanical dynamic characteristics of the prime mover. In step S2, when creating the generator model, motor model, power battery model, and propeller model, the generator model, motor model, power battery model, and propeller model created in the AMESim platform are used as sub-models. The main model and the sub-model interact with each other through a joint simulation interface on the MATLAB / Simulink platform and the AMESim platform.

[0030] In a preferred embodiment of this application, the main model and the sub-model interact with each other through a co-simulation interface of the MATLAB / Simulink platform and the AMESim platform, specifically including: The engine model in the MATLAB / Simulink platform transmits the power turbine output torque and speed signals to the generator model in the AMESim platform; the generator model in the AMESim platform feeds back the power generation demand and mechanical load torque to the MATLAB / Simulink platform; the motor model receives the power command and outputs the mechanical torque and speed to the propeller model, and the propeller model feeds back the load characteristics to the motor model.

[0031] This embodiment addresses the characteristics of hybrid electric propulsion systems involving multiple disciplines and professional modeling tools by designing an overall architecture for a multidisciplinary mathematical model, with MATLAB as the main model and AMESim as the secondary model.

[0032] Specifically, a component-level full-state dynamic mathematical model of a dual-shaft free-turbine turboshaft engine is established in the MATLAB / Simulink platform as the main model of the entire hybrid electric propulsion system, responsible for providing the aerodynamic, thermodynamic, and mechanical dynamic characteristics of the prime mover. In the AMESim platform, a megawatt-level permanent magnet synchronous generator model, a permanent magnet synchronous motor model, a dynamic equivalent circuit model of the power battery, and a propeller aerodynamic model based on dimensionless characteristics are established as secondary models. The generator and motor models are designed based on average electrical and steady-state mechanical characteristics, avoiding the use of high-frequency transient models to improve simulation efficiency. The power battery model uses a dynamic equivalent circuit (including open-circuit voltage, internal resistance, and multiple RC units) to characterize its voltage and current response dynamics. The propeller models are divided into variable-pitch thrust propellers and fixed-pitch lift propellers, and functional relationships between thrust coefficient, power coefficient, advance ratio, and pitch angle are established for each.

[0033] The main model and the sub-models interact via a MATLAB / AMESim co-simulation interface. The engine model in MATLAB transmits the turbine output torque and speed signals to the generator model in AMESim, while the generator model in AMESim feeds back the power demand and mechanical load torque to MATLAB. The motor model receives power commands and outputs mechanical torque and speed to the propeller model, which in turn feeds back the load characteristics to the motor. This architecture effectively integrates and co-simulates specialized mathematical models of the engine, generator, motor, power battery, and propeller.

[0034] In a preferred embodiment of this application, when establishing the component-level full-state dynamic model of the turboshaft engine in step S1 to obtain the engine model, the engine model obtained by establishing the component-level full-state dynamic model of the turboshaft engine in the MATLAB / Simulink platform is used as the main model of the entire hybrid electric propulsion system, responsible for providing the aerodynamic, thermodynamic, and mechanical dynamic characteristics of the prime mover; when establishing the generator model, electric motor model, power battery model, and propeller model in step S2, the generator model, electric motor model, power battery model, and propeller model established in the Dymola platform are used as secondary models; the main model and secondary models achieve data interaction through joint simulation via the FMI / FMU standard interface.

[0035] In a preferred embodiment of this application, when establishing the component-level full-state dynamic model of the turboshaft engine in step S1 to obtain the engine model, the engine model obtained by establishing the component-level full-state dynamic model of the turboshaft engine in the NPSS platform is used as the main model of the entire hybrid electric propulsion system, responsible for providing the aerodynamic, thermodynamic and mechanical dynamic characteristics of the prime mover; when establishing the generator model, electric motor model, power battery model and propeller model in step S2, the generator model, electric motor model, power battery model and propeller model established in the MATLAB / SimPowerSystems platform are used as secondary models; the main model and secondary models achieve data interaction through joint simulation via the MATLAB interface provided by NPSS.

[0036] This application addresses the significant difference in dynamic response timescales between turboshaft engines (second-level response) and generators, motors, and power batteries (millisecond-level response). It proposes a set of measures to rationally allocate the equivalent dynamic response levels of the mathematical models for each component. Specifically, these measures include: First, for the turboshaft engine model, retaining the complete rotor dynamics equations and cavity dynamics equations, enabling it to realistically reflect the second-level dynamic response characteristics of parameters such as speed, temperature, and pressure during power changes. Second, for the generator and motor models, abandoning high-frequency transient models (such as PWM details with switching frequencies exceeding 10kHz), adopting mathematical models based on average electrical characteristics and steady-state mechanical characteristics. Specifically, the input electrical power of the motor is converted to mechanical power through efficiency, and the input mechanical power of the generator is converted to electrical power through efficiency. A torque limit line composed of maximum output mechanical power, maximum output torque, and maximum operating speed is introduced, setting the equivalent dynamic response time of the electrical model to the tens to hundreds of milliseconds range. Third, for the power battery model, a dynamic equivalent circuit is used to characterize its voltage and current responses, dynamically equating electrochemical reactions and solid-phase diffusion processes to the charging and discharging processes of an RC network, setting the equivalent response time to the seconds to tens of seconds range. Finally, for the propeller model, a steady-state aerodynamic model based on dimensionless characteristics (thrust coefficient, power coefficient) is adopted, whose dynamic response is dominated by the mechanical dynamics of the electric motor. Through the above method, this application reasonably allocates the equivalent levels of dynamic response for the mathematical models of the engine, generator, electric motor, power battery, and propeller: the engine model retains realistic second-level response characteristics, the electrical model is moderately simplified to a response level of hundreds of milliseconds, and the battery model retains a state-of-charge change process of tens of seconds. This satisfies the dynamic response requirements of the overall control and energy management design of the hybrid electric propulsion system, while preserving the technical characteristics of each discipline to the greatest extent possible, and ensuring the computational efficiency of the digital simulation.

[0037] In a preferred embodiment of this application, a full-state control law covering the entire process and state of a hybrid electric propulsion system from start-up from rest, load increase / decrease to shutdown is designed. This includes the full-state control law for the engine, the generator, and the electric motor. For a twin-shaft free-turbine turboshaft engine, a full-state control law comprising six stages / modes is designed, specifically as follows: In step S3, when designing the ground start control law for the engine, for a turboshaft engine, the ground start process requires coordinated adjustment of the output shaft load, starter, ignition device, and starting fuel flow, among which: The output shaft load is generally set to the minimum position during startup. The angle of the load bar is used This means that the following formula must be satisfied: ; The starter motor adjustment principle is as follows: When the start button is pressed while the machine is stationary, the controller sends a command to activate the starter motor. ; When the gas turbine speed Reaching disengagement speed The controller issues a command to disconnect the starter motor. ; The starter motor adjustment law is expressed by the following formula: ; The adjustment rules for the ignition device are as follows: When the gas turbine speed is lower than the ignition speed The controller issues an ignition shut-off command. ; When the gas turbine speed reaches the ignition speed That is, the controller sends an ignition command to the ignition device. The ignition device releases high voltage to the ignition nozzle, which breaks down the air and generates a high-energy electric spark. When ignition duration Reaching the limit value The controller issues an ignition shut-off command. This is to ensure the lifespan of the ignition accessories; The adjustment law of the ignition device is expressed by the following formula: ; The starting fuel adjustment rule is as follows: After starting, when the gas turbine speed reaches the fuel injection speed driven by the starter motor... At that time, the controller provides the ignition fuel flow rate. The target instruction is to use the small closed-loop control of the fuel regulator needle to adjust the position of the metering needle and provide the ignition flow rate. When the gas turbine speed Lower than ground idle speed When the control domain is △, the open-loop fuel supply law of the air-fuel ratio is adopted, and the fuel regulator accurately supplies fuel to the engine through a small closed-loop metering. The starting fuel adjustment law is expressed by the following formula. Power factor: ; The ground idle control law is as follows: When the gas turbine speed enters the ground idle speed control range, closed-loop control of the gas turbine speed is adopted, and the starting fuel regulation law is expressed by the following formula: ; The ground / air idle transition control principle is as follows: When transitioning from ground idle to air idle, the control mode changes from gas turbine shaft speed control to power turbine speed control, employing a dual-loop configuration: the desired gas turbine speed is obtained through a closed-loop power turbine speed control. Then adjust the fuel flow to increase the power turbine speed. n p Target value reached The expression is as follows: ; ; The load control principle is as follows: When loading or unloading, load change feedforward is introduced to reduce the output shaft speed fluctuation caused by load changes to a reasonable range, as expressed by the following formula: ; in, L ds For the load bar angle, L ds,cmd For instruction value, △L ds This represents the change in load arm angle relative to the previous command cycle. m f0 This refers to the fuel flow rate obtained solely based on dual-loop control. The parking control principle is as follows: when the vehicle is at a slow speed on the ground, the fuel supply is directly cut off, as expressed by the following formula: ; The limiting protection control is as follows: supplementary turbine inter-temperature over-temperature limit. Fuel flow restriction Fuel flow shutdown limit and fuel change rate limit The security protection logic is expressed by the following formula: ; The generator control principle is as follows: the generator speed is stabilized by adjusting the generator's input torque. Obtain output current control command Under preset output voltage conditions, the output current can be controlled. Control of power generation: ; The control principle of the electric motor is as follows: when the circuit voltage is determined, the output torque control command is obtained. T rq,m,cmd By adjusting the input current of the motor To obtain the required output torque and mechanical power: .

[0038] The above-mentioned full-state control law effectively realizes the driving and control of the entire process and state of the hybrid electric propulsion system from start-up, load increase / decrease to shutdown from a stationary state.

[0039] In a preferred embodiment of this application, considering the structural characteristics of the series hybrid electric propulsion system, a full-condition energy management strategy based on the dynamic response capability of the generator system is designed. This strategy can provide a reasonable power combination scheme for the electric propeller in real time according to flight control commands, achieving switching and stable operation of four working modes. The core innovation of the energy management strategy lies in: based on the power generation response capability of the series dual-shaft turboshaft generator system, a reasonable power loading rate constraint and unloading rate constraint suitable for all working conditions are designed, coordinating the dynamic response capabilities of each component. The specific strategy is as follows: In step S4, the power allocation rule in pure electric mode is: the output power demand command sent to the generator controller. The state of charge (SOC) is 0 in this mode, which ensures the state of charge of the power battery. Not lower than the minimum limit value : ; The power allocation rule in the eddy electric hybrid mode is as follows: the generator controller output power requirement is the total propeller electric power requirement. Considering the limited dynamic response capability of eddy current electronic systems, the rate of change of generator power demand command should not exceed the maximum load rate. Not lower than the minimum unloading rate The rate of change of the generator power demand command is determined by the dynamic response capability of the eddy current system. Let: ; In the eddy electric hybrid mode, the generator controller power demand command for: ; The power allocation rule for the series hybrid mode is: the power generation demand command ensures that the eddy current system maintains maximum power generation capacity. The power battery will automatically compensate for the power difference required by the propeller, and at this time, the state of charge of the power battery must also be maintained. S oc It must not be lower than the state of charge limit value S oc,min : ; The power allocation rule for the charging hybrid mode is as follows: the power generation demand command is the electric power required by the propeller and the charging power of the power battery. The sum, taking into account the dynamic response capability of the eddy current system, and also considering the avoidance of overcharging of the power battery, that is: When the power battery is not fully charged, it is charged according to the given charging power. Charge: ; Once the battery is fully charged, it will stop charging. ; In charging hybrid mode, the sum of all required electrical power for: ; make: ; The power generation demand command in the charging hybrid mode is: .

[0040] The core of the above energy management strategy lies in embedding the limited power loading / unloading rate of the generator system as a constraint into the power distribution logic, so that the engine can respond smoothly to power changes within its dynamic capability range, and the rapid power fluctuations exceeding the capability range are borne by the power battery, thereby achieving better power supply coordination under all operating conditions.

[0041] This application has been thoroughly verified, proving that the technical solution is feasible.

[0042] First, the mathematical models of each component were experimentally verified. The mathematical models of the turboshaft engine, generator, lift electric propulsion subsystem, and thrust electric propulsion subsystem were compared and verified with experimental platform test data. Next, the dynamic operating conditions of the hybrid electric propulsion system were coupled and verified. Verification results show that the multidisciplinary mathematical model established in this application can accurately reflect the steady-state and dynamic characteristics of the hybrid electric propulsion system. The control strategy can achieve stable operation of multiple energy sources, and the energy management scheme effectively balances power demand and energy efficiency. The model accuracy meets engineering simulation requirements (all deviations are less than 5%), and the control performance meets engineering application indicators (steady-state error <0.5%, dynamic overshoot <5%). The modeling, control, and simulation methods proposed in this application can provide reliable theoretical and technical support for the design, simulation, and control of turboshaft-based hybrid electric propulsion systems for large eVTOL and medium-to-large electric aircraft. Specific verification results can be seen in the simulation results. To further investigate the steady-state and dynamic coupling effects among the components of the hybrid electric propulsion system, the aforementioned integrated mathematical model was used, under standard day conditions at sea level, according to... Figure 3 and Figure 4 The results show that by changing the lift propeller speed, thrust propeller speed, and pitch angle, digital simulations were conducted to study different operating modes of the entire hybrid electric propulsion system. Figure 3 and Figure 4 As shown, the lift propeller is a fixed-pitch propeller. Gradually increasing its rotational speed increases the load power demand, thus testing the hybrid electric propulsion system's response to the lift propeller. The thrust propeller is a variable-pitch propeller, operating at a constant rotational speed. Gradually increasing its pitch tests the hybrid electric propulsion system's response to the thrust propeller.

[0043] eddy current hybrid mode: In the simulation test, the engine was first started to idle state, then the eddy electric hybrid mode was selected through the energy management device, and then... Figure 3 Gradually change the lift propeller speed requirement, then first change the thrust propeller speed requirement to its maximum, and then... Figure 4 By gradually changing the collective pitch angle of the thruster, the following results were obtained. Figure 5 and Figure 6 As shown, after the engine enters idle mode, the engine gas turbine speed changes with the desired rotational speeds of the lift propeller and thrust propeller under the coordinated control strategy of eddy current mode. The power turbine drives the generator to provide all the power required by the propeller; the battery SOC remains almost unchanged.

[0044] Pure electric mode: Pure electric mode should be a short-term backup power source when the engine power is insufficient or the engine is not working. Figure 7 and Figure 8The simulation results show that when the engine is in idle flight mode, the desired speed and pitch of the thrust propeller and lift propeller are gradually changed. Under the coordinated control strategy of pure electric mode, the power output of the engine to the generator is 0, and the speed of the gas turbine and power turbine remains constant. The propeller motor is fully driven by the power battery and quickly stabilizes at the desired value, and the state of charge of the power battery decreases accordingly.

[0045] Series hybrid mode: According to the energy management strategy of the hybrid system, in series hybrid mode, the engine delivers a maximum of the set electrical power. When more power is needed, the battery provides the additional power. Digital simulation results are shown in Figure 9. Figure 10 As shown, when the engine enters idle mode, with the changes in the desired speeds of the lift propeller and thrust propeller and the pitch angle, under the coordinated control strategy of hybrid mode, when the power demand of the propeller motor is lower than the preset capability limit of the engine, the steady-state power demand of the propeller is entirely provided by the generator, and the power battery provides transient compensation; when the power demand of the propeller exceeds the capability limit of the engine, the power of the generator remains unchanged, and the additional energy demand is provided by the power battery.

[0046] Charging Hybrid Mode: To simulate a hybrid charging mode, firstly, under standard sea-level weather conditions, pure electric mode was used to reduce the state of charge of the power turbine. Then, hybrid charging mode was used, allowing the engine to provide charging power to restore the power battery. Finally, hybrid charging mode was exited. The specific process is as follows: Figure 11 and Figure 12 As shown, once the engine enters idle mode, it gradually changes the desired propeller speed and pitch. Under the coordinated control strategy in pure electric mode, the propeller motor's power demand is entirely provided by the battery, causing the battery's state of charge (SOC) to decrease. Then, in charging mode, under the coordinated control strategy, the engine improves its SOC, causing the generator to output a constant charging power. The battery's SOC gradually increases, and when it reaches 100%, the generator output power is zero, and charging of the battery ceases.

[0047] like Figure 13 As shown, another preferred embodiment of this application provides a simulation device for a hybrid electric propulsion system, comprising: The main model building module is used to build a component-level full-state dynamic model of the turboshaft engine to obtain the engine model. This includes using the full-state component method, based on the cavity dynamics equation, rotor dynamics equation and variable specific heat calculation method, to build a nonlinear differential equation model that can reflect the entire process of the engine from static start-up, load increase / decrease to shutdown in the selected main simulation platform. The sub-model building module is used to build generator models, motor models, power battery models and propeller models. It includes building average characteristic models of megawatt-level permanent magnet synchronous generators and motors based on average electrical characteristics and steady-state mechanical characteristics in the selected sub-simulation platform, building dynamic equivalent circuit models of power batteries, and building aerodynamic models of variable-pitch thrust propellers and fixed-pitch lift propellers based on dimensionless characteristics. The full-state control law construction module is used to design the full-state control laws of the hybrid electric propulsion system, including the engine full-state control laws, generator control laws, and electric motor control laws. The engine full-state control laws include the engine ground start control law, ground idle control law, ground idle / air idle conversion control law, load increase / decrease control law, shutdown control law, and limit protection control logic. The full-condition energy management strategy construction module is used to design a full-condition energy management strategy that takes into account dynamic response capabilities. This includes setting power allocation rules for four working modes—eddy electric hybrid mode, series hybrid mode, pure electric mode, and charging hybrid mode—based on the maximum loading rate and minimum unloading rate of the generator system, so as to realize coordinated power allocation between the generator and the power battery. The model integration and co-simulation verification module is used to integrate multi-disciplinary models and conduct co-simulation verification. This includes integrating the engine model with the generator model, electric motor model, power battery model and propeller model through the simulation co-simulation interface, setting simulation working condition sequences, running simulations and comparing the test data of each component with the prototype to verify the accuracy of the model and the effectiveness of the control strategy.

[0048] The simulation device for a hybrid electric propulsion system provided in this embodiment employs the simulation method for hybrid electric propulsion systems described in the above embodiments, addressing the technical problems of existing technologies lacking a unified simulation architecture, equivalent synergy of multidisciplinary responses, full coverage of control laws, and constraints on energy management strategies. Compared with existing technologies, the beneficial effects of the simulation device for a hybrid electric propulsion system provided in this embodiment are the same as those of the simulation method for a hybrid electric propulsion system provided in the above embodiments, and other technical features in the simulation device for a hybrid electric propulsion system are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0049] like Figure 14 As shown, a preferred embodiment of this example also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the simulation method for the hybrid electric propulsion system in the above embodiment.

[0050] This embodiment also provides an electronic device that uses the simulation method of the hybrid electric propulsion system in the above embodiments to solve the technical problems of the lack of a unified simulation architecture, equivalent coordination of multi-disciplinary response, full coverage control law, and energy management strategy constraints in the prior art. Compared with the prior art, the beneficial effects of the electronic device provided in this embodiment are the same as the beneficial effects of the simulation method of the hybrid electric propulsion system provided in the above embodiments, and other technical features in the electronic device are the same as the features disclosed in the method of the above embodiments, which will not be repeated here.

[0051] like Figure 15 As shown, a preferred embodiment of this application also provides a computer device, which may be a terminal or a liveness detection server, and its internal structure diagram may be as follows. Figure 15 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The network interface is used to communicate with other external computer devices via a network connection. When the computer program is executed by the processor, it implements the steps of the simulation method for the hybrid electric propulsion system described above.

[0052] Those skilled in the art will understand that Figure 15 The structure shown is merely a block diagram of a portion of the structure related to the solution of this embodiment, and does not constitute a limitation on the computer device to which the solution of this embodiment is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0053] The computer device provided in this embodiment adopts the simulation method of the hybrid electric propulsion system in the above embodiment to solve the technical problems of the lack of unified simulation architecture, equivalent coordination of multi-disciplinary response, full coverage control law, and energy management strategy constraints in the prior art. Compared with the prior art, the beneficial effects of the computer device provided in this embodiment are the same as the beneficial effects of the simulation method of the hybrid electric propulsion system provided in the above embodiment. In addition, other technical features in the electronic device are the same as the features disclosed in the method of the above embodiment, and will not be repeated here.

[0054] A preferred embodiment of this application also provides a storage medium including a stored program that, when the program is executed, controls the device where the storage medium is located to perform the steps of the simulation method for the hybrid electric propulsion system in the above embodiments.

[0055] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0056] If the functions described in this embodiment are implemented as software functional units and sold or used as independent products, they can be stored in one or more computing device-readable storage media. Based on this understanding, the parts of this embodiment that contribute to the prior art or the technical solution can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computing device (which may be a personal computer, server, mobile computing device, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this embodiment. The aforementioned storage media include: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0057] Those skilled in the art will understand that the embodiments of this example can be provided as methods, systems, or computer program products. Therefore, this example can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this example can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code. The solutions in this example can be implemented using various computer languages, such as the object-oriented programming language C++ and the embedded programming language C.

[0058] This embodiment is described with reference to flowchart illustrations and / or block diagrams of the method, apparatus (system), and computer program product according to this embodiment. It should be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0059] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction set implemented in a process. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0060] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0061] This embodiment also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the simulation method for a hybrid electric propulsion system as described above.

[0062] The computer program product provided in this embodiment addresses the technical problems of existing technologies, such as the lack of a unified simulation architecture, equivalent synergy of multidisciplinary responses, full coverage of control laws, and constraints on energy management strategies. Compared with existing technologies, the beneficial effects of the computer program product provided in this embodiment are the same as those of the simulation method for hybrid electric propulsion systems provided in the above embodiments, and will not be elaborated upon here.

[0063] In addition, there are several alternative solutions to this application, all of which fall within the scope of protection of this application: (1) Alternatives to multidisciplinary joint simulation architecture This application adopts an architecture with MATLAB as the main model and AMESim as the secondary model. Alternative solutions may include: ① Using MATLAB / Simulink as the main model and Dymola (based on Modelica language) as the secondary model to build an electrical and thermal management system model, and performing co-simulation through the FMI / FMU standard interface; ② Using NPSS (Digital Propulsion System Simulation) as the main model to build an engine dynamic model and MATLAB / SimPowerSystems as the secondary model to build an electrical system model, and performing co-simulation through the MATLAB interface provided by NPSS; ③ Using a single platform (such as Simcenter Amesim or GT-SUITE) to simultaneously build engine thermodynamic and electrical models, achieving multi-disciplinary integration on the same platform, but this solution requires a high level of cross-disciplinary modeling capability from the single software.

[0064] (2) Alternatives to the multidisciplinary model dynamic response equivalent collaborative method: This application achieves dynamic equivalence by abandoning the high-frequency transient details of the motor, adopting an average characteristic model, and introducing a torque limit line. Alternatives may include: ① Using a simplified electromagnetic transient model based on the dq axis equation for the motor and generator (retaining the basic dynamics of rotor field-oriented control, but ignoring PWM switching harmonics), with the dynamic response time set to 10-20 milliseconds; ② Using an improved equivalent circuit model for the power battery (such as adding more RC parallel branches to simulate polarization processes with different time constants), or using a mechanism-based electrochemical-thermal coupling reduced-order model; ③ Using a linear variable parameter model or state-space model to replace the component-level nonlinear model for the engine dynamic response, improving simulation efficiency while retaining the dominant dynamic characteristics through model reduction.

[0065] (3) Alternative solutions to the full-state control law: This application provides specific control law expressions (Equations (26)-(35)). Alternative solutions may include: ① In the ground start-up phase, adopting closed-loop fuel regulation combined with ignition detection adaptive start-up control instead of open-loop fuel-air ratio fuel supply; ② In the load increase and decrease phase, adopting model predictive control (MPC) based feedforward-feedback composite control instead of simple load feedforward compensation; ③ Adopting cross-limit protection logic of power turbine speed and gas turbine speed instead of independent over-temperature and shutdown limits; ④ The control of generator and motor can adopt direct torque control or model predictive current control instead of the simple current / torque regulation in this application.

[0066] (4) Alternative solutions to the full-condition energy management strategy: This application is based on the load / unload rate constraint of the generator system for power allocation. Alternative solutions may include: ① Introducing an adaptive rate limit based on the real-time state of the engine (such as exhaust temperature margin, rotor acceleration) so that the rate of change of generator power can be dynamically adjusted; ② Using energy management based on optimization algorithms (such as dynamic programming, equivalent fuel consumption minimization strategy) and implementing it by looking up tables on the basis of offline optimization; ③ Adding feedback adjustment of battery state of charge (SOC) so that the charging power changes with the SOC in an S-shaped curve; ④ In hybrid mode, introducing short-term prediction of propeller power demand and adjusting generator power in advance to reduce the peak power demand of the battery.

[0067] Obviously, those skilled in the art can make various modifications and variations to this embodiment without departing from the spirit and scope of this embodiment. Therefore, if these modifications and variations of this embodiment fall within the scope of the claims of this embodiment and their equivalents, this embodiment is also intended to include these modifications and variations.

Claims

1. A simulation method for a hybrid electric propulsion system, characterized in that, Includes the following steps: S1. Establish a component-level full-state dynamic model of the turboshaft engine to obtain the engine model. This includes using the full-state component method, based on the cavity dynamics equation, rotor dynamics equation and variable specific heat calculation method, to establish a nonlinear differential equation model that can reflect the entire process of the engine from static start-up, load increase / decrease to shutdown in the selected main simulation platform. S2. Establish generator model, motor model, power battery model and propeller model, including in the selected sub-simulation platform, establish the average characteristic model of megawatt-level permanent magnet synchronous generator and motor based on average electrical characteristics and steady-state mechanical characteristics, establish the dynamic equivalent circuit model of power battery, and establish the aerodynamic model of variable pitch thrust propeller and fixed pitch lift propeller based on dimensionless characteristics. S3. Design the full-state control law of the hybrid electric propulsion system, including the full-state control law of the engine, the control law of the generator and the control law of the electric motor. The full-state control law of the engine includes the ground start control law of the engine, the ground idle control law, the ground idle / air idle conversion control law, the load increase / decrease control law, the shutdown control law, and the limitation and protection control logic. S4. Design a full-condition energy management strategy that considers dynamic response capability, including setting power distribution rules for four working modes: eddy electric hybrid mode, series hybrid mode, pure electric mode, and charging hybrid mode, based on the maximum loading rate and minimum unloading rate of the generator system, to achieve coordinated power distribution between the generator and the power battery. S5. Integrate multidisciplinary models and conduct joint simulation verification, including integrating the engine model with the generator model, electric motor model, power battery model and propeller model through the simulation joint simulation interface, setting simulation working condition sequence, running simulation and comparing the test data of each component with the prototype to verify the accuracy of the model and the effectiveness of the control strategy.

2. The simulation method for a hybrid electric propulsion system according to claim 1, characterized in that, When establishing the component-level full-state dynamic model of the turboshaft engine in step S1 to obtain the engine model, the engine model obtained by establishing the component-level full-state dynamic model of the turboshaft engine in the MATLAB / Simulink platform is used as the main model of the entire hybrid electric propulsion system, which is responsible for providing the aerodynamic, thermodynamic and mechanical dynamic characteristics of the prime mover. In step S2, when creating the generator model, motor model, power battery model, and propeller model, the generator model, motor model, power battery model, and propeller model created in the AMESim platform are used as sub-models. The main model and the sub-model interact with each other through a joint simulation interface on the MATLAB / Simulink platform and the AMESim platform.

3. The simulation method for a hybrid electric propulsion system according to claim 2, characterized in that, The main model and the sub-model interact with each other through a joint simulation interface on the MATLAB / Simulink and AMESim platforms, specifically including: The engine model in the MATLAB / Simulink platform transmits the power turbine output torque and speed signals to the generator model in the AMESim platform; the generator model in the AMESim platform feeds back the power generation demand and mechanical load torque to the MATLAB / Simulink platform; the motor model receives the power command and outputs the mechanical torque and speed to the propeller model, and the propeller model feeds back the load characteristics to the motor model.

4. The simulation method for a hybrid electric propulsion system according to claim 1, characterized in that, In step S1, when establishing the component-level full-state dynamic model of the turboshaft engine to obtain the engine model, the engine model obtained by establishing the component-level full-state dynamic model of the turboshaft engine in the MATLAB / Simulink platform is used as the main model of the entire hybrid electric propulsion system, responsible for providing the aerodynamic, thermodynamic and mechanical dynamic characteristics of the prime mover; in step S2, when establishing the generator model, electric motor model, power battery model and propeller model, the generator model, electric motor model, power battery model and propeller model established in the Dymola platform are used as sub-models; The main model and the sub-model achieve data interaction through joint simulation via the FMI / FMU standard interface; or, In step S1, when establishing the component-level full-state dynamic model of the turboshaft engine to obtain the engine model, the engine model obtained from the component-level full-state dynamic model of the turboshaft engine in the NPSS platform is used as the main model of the entire hybrid electric propulsion system, responsible for providing the aerodynamic, thermodynamic, and mechanical dynamic characteristics of the prime mover; in step S2, when establishing the generator model, electric motor model, power battery model, and propeller model, the generator model, electric motor model, power battery model, and propeller model established in the MATLAB / SimPowerSystems platform are used as sub-models. The main model and the sub-model achieve data interaction through joint simulation via the MATLAB interface provided by NPSS.

5. The simulation method for a hybrid electric propulsion system according to claim 1, characterized in that, In step S3, when designing the ground start control law for the engine, for a turboshaft engine, the ground start process requires coordinated adjustment of the output shaft load, starter, ignition device, and starting fuel flow, among which: The output shaft load is generally set to the minimum position during startup. The angle of the load bar is used This means that the following formula must be satisfied: ； The starter motor adjustment principle is as follows: When the start button is pressed while the machine is stationary, the controller sends a command to activate the starter motor. ; When the gas turbine speed Reaching disengagement speed The controller issues a command to disconnect the starter motor. ; The starter motor adjustment law is expressed by the following formula: ； The adjustment rules for the ignition device are as follows: When the gas turbine speed is lower than the ignition speed The controller issues an ignition shut-off command. ; When the gas turbine speed reaches the ignition speed That is, the controller sends an ignition command to the ignition device. The ignition device releases high voltage to the ignition nozzle, which breaks down the air and generates a high-energy electric spark. When ignition duration Reaching the limit value The controller issues an ignition shut-off command. This is to ensure the lifespan of the ignition accessories; The adjustment law of the ignition device is expressed by the following formula: ； The starting fuel adjustment rule is as follows: After starting, when the gas turbine speed reaches the fuel injection speed driven by the starter motor... At that time, the controller provides the ignition fuel flow rate. The target instruction is to use the small closed-loop control of the fuel regulator needle to adjust the position of the metering needle and provide the ignition flow rate. When the gas turbine speed Lower than ground idle speed When the control domain is △, the open-loop fuel supply law of the air-fuel ratio is adopted, and the fuel regulator accurately supplies fuel to the engine through a small closed-loop metering. The starting fuel adjustment law is expressed by the following formula. Power factor: ； The ground idle control law is as follows: When the gas turbine speed enters the ground idle speed control range, closed-loop control of the gas turbine speed is adopted, and the starting fuel regulation law is expressed by the following formula: ； The ground / air idle transition control principle is as follows: When transitioning from ground idle to air idle, the control mode changes from gas turbine shaft speed control to power turbine speed control, employing a dual-loop configuration: the desired gas turbine speed is obtained through a closed-loop power turbine speed control. Then adjust the fuel flow to increase the power turbine speed. n p Target value reached The expression is as follows: ； ； The load control principle is as follows: When loading or unloading, load change feedforward is introduced to reduce the output shaft speed fluctuation caused by load changes to a reasonable range, as expressed by the following formula: ； in, L ds For the load bar angle, L ds,cmd For instruction value, △L ds This represents the change in load arm angle relative to the previous command cycle. m f0 This refers to the fuel flow rate obtained solely based on dual-loop control. The parking control principle is as follows: when the vehicle is at a slow speed on the ground, the fuel supply is directly cut off, as expressed by the following formula: ； The limiting protection control is as follows: supplementary turbine inter-temperature over-temperature limit. Fuel flow restriction Fuel flow shutdown limit and fuel change rate limit The security protection logic is expressed by the following formula: 。 6. The simulation method for a hybrid electric propulsion system according to claim 5, characterized in that, In step S3, the generator control law is as follows: the generator speed is stabilized by adjusting the generator's input torque. Obtain output current control command Under preset output voltage conditions, the output current can be controlled. Control of power generation: ； The control principle of the electric motor is as follows: when the circuit voltage is determined, the output torque control command is obtained. T rq,m,cmd By adjusting the input current of the motor To obtain the required output torque and mechanical power: 。 7. The simulation method for a hybrid electric propulsion system according to claim 1, characterized in that, In step S4, the power allocation rule in pure electric mode is: the output power demand command sent to the generator controller. The state of charge (SOC) is 0 in this mode, which ensures the state of charge of the power battery. Not lower than the minimum limit value : ； The power allocation rule in the eddy electric hybrid mode is as follows: the generator controller output power requirement is the total propeller electric power requirement. Considering the limited dynamic response capability of eddy current electronic systems, the rate of change of generator power demand command should not exceed the maximum load rate. Not lower than the minimum unloading rate The rate of change of the generator power demand command is determined by the dynamic response capability of the eddy current system. Let: ； In the eddy electric hybrid mode, the generator controller power demand command for: ； The power allocation rule for the series hybrid mode is: the power generation demand command ensures that the eddy current system maintains maximum power generation capacity. The power battery will automatically make up for the difference in power demand from the propeller, and at this time, the state of charge of the power battery must also be maintained. S oc It must not be lower than the state of charge limit value S oc,min : ； The power allocation rule for the charging hybrid mode is as follows: the power generation demand command is the electric power required by the propeller and the charging power of the power battery. The sum, taking into account the dynamic response capability of the eddy current system, and also considering the avoidance of overcharging of the power battery, that is: When the power battery is not fully charged, it is charged according to the given charging power. Charge: ； Once the battery is fully charged, it will stop charging. ； In the charging hybrid mode, the sum of all required electric power for: ； make: ； The power generation demand command in the charging hybrid mode is: 。 8. A simulation device for a hybrid electric propulsion system, characterized in that, include: The main model building module is used to build a component-level full-state dynamic model of the turboshaft engine to obtain the engine model. This includes using the full-state component method, based on the cavity dynamics equation, rotor dynamics equation and variable specific heat calculation method, to build a nonlinear differential equation model that can reflect the entire process of the engine from static start-up, load increase / decrease to shutdown in the selected main simulation platform. The sub-model building module is used to build generator models, motor models, power battery models and propeller models. It includes building average characteristic models of megawatt-level permanent magnet synchronous generators and motors based on average electrical characteristics and steady-state mechanical characteristics in the selected sub-simulation platform, building dynamic equivalent circuit models of power batteries, and building aerodynamic models of variable-pitch thrust propellers and fixed-pitch lift propellers based on dimensionless characteristics. The full-state control law construction module is used to design the full-state control laws of the hybrid electric propulsion system, including the engine full-state control laws, generator control laws, and electric motor control laws. The engine full-state control laws include the engine ground start control law, ground idle control law, ground idle / air idle conversion control law, load increase / decrease control law, shutdown control law, and limit protection control logic. The full-condition energy management strategy construction module is used to design a full-condition energy management strategy that takes into account dynamic response capabilities. This includes setting power allocation rules for four working modes—eddy electric hybrid mode, series hybrid mode, pure electric mode, and charging hybrid mode—based on the maximum loading rate and minimum unloading rate of the generator system, so as to realize coordinated power allocation between the generator and the power battery. The model integration and co-simulation verification module is used to integrate multi-disciplinary models and conduct co-simulation verification. This includes integrating the engine model with the generator model, electric motor model, power battery model and propeller model through the simulation co-simulation interface, setting simulation working condition sequences, running simulations and comparing the test data of each component with the prototype to verify the accuracy of the model and the effectiveness of the control strategy.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the simulation method for the hybrid electric propulsion system as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the simulation method for the hybrid electric propulsion system as described in any one of claims 1 to 7.

Images