Distributed electric aircraft risk source determination method and system based on flight profile

Abstract

This application provides a method and system for determining risk sources of distributed electric aircraft based on flight profiles, applied in the field of aircraft simulation technology. It includes: acquiring the overall construction content of the flight profile and topology of the distributed electric aircraft, and obtaining typical operating conditions for each stage in multiple phases corresponding to the flight profile. The overall construction content includes a high-power-density battery pack, a DC-DC buck converter, an electronic speed controller, a DC brushless motor, and rotors / propellers; simulating the mathematical model of the overall construction content under the target typical operating conditions of the target phase, obtaining simulation results for the target typical operating conditions; and accurately determining the flight test risk sources of the distributed electric aircraft under the target typical operating conditions from the high-power-density battery pack, DC-DC buck converter, electronic speed controller, DC brushless motor, and rotors / propellers based on the simulation results. This significantly reduces the flight risk of new aircraft configurations (i.e., distributed electric aircraft) and improves flight test efficiency.

Description

Technical Field

[0001] This application relates to the field of aircraft simulation technology, and in particular to a method and system for determining risk sources of distributed electric aircraft based on flight profiles. Background Technology

[0002] With the rapid development of aviation technology, distributed electric propulsion systems, with their advantages of high efficiency, high redundancy, and low noise, have become the core power solution for low-altitude aircraft such as compound wing aircraft and electric vertical takeoff and landing (eVTOL) aircraft. The distributed layout, through the coordinated operation of multiple rotors / propellers, greatly enhances the performance of distributed electric aircraft.

[0003] However, in actual engineering applications and aircraft simulation, current methods for determining risk sources of distributed electric aircraft lack a full-link dynamic coupling simulation model, which makes it impossible to accurately determine risk sources in flight tests. At the same time, they face extremely high uncontrollable risks and economic costs, and the accumulation of safety boundary data under complex working conditions is seriously lagging behind. Existing single verification methods are difficult to support the high standard of airworthiness certification requirements. Summary of the Invention

[0004] This application provides a method and system for determining risk sources of distributed electric aircraft based on flight profiles. Addressing the complex electromechanical coupling characteristics of distributed electric aircraft, this method constructs a mathematical model of the overall structure of the distributed electric aircraft and performs in-depth simulations of typical operating conditions across the entire flight profile. This accurately identifies risk sources for flight testing of the distributed electric aircraft under specific typical operating conditions, significantly reducing the flight risk of new aircraft configurations (i.e., distributed electric aircraft), improving flight test efficiency, and ultimately achieving quantitative performance evaluation throughout the entire lifecycle. It provides detailed and multi-dimensional data support for determining safety boundaries and obtaining airworthiness certification under complex operating conditions, overcoming the shortcomings of existing methods such as insufficient verification, high R&D costs, and a lack of data accumulation.

[0005] This application provides a method for determining risk sources of distributed electric aircraft based on flight profiles, including: The flight profile and topology of the distributed electric aircraft are obtained, and the typical operating conditions of each stage in the multiple stages corresponding to the flight profile and the overall construction content corresponding to the topology are obtained. The overall construction content includes a high power density battery pack, a DC-DC buck converter, an electronic speed controller, a DC brushless motor, and a rotor / propeller. Under the target typical operating conditions of the target stage, the mathematical models of the high power density battery pack, the DC buck converter, the electronic speed controller, the DC brushless motor and the rotor / propeller are simulated to obtain the simulation results corresponding to the target typical operating conditions. The target stage is any one of the multiple stages. Based on the simulation results corresponding to the target typical operating conditions, the flight test risk sources of the distributed electric aircraft under the target typical operating conditions are determined from the high power density battery pack, the DC buck converter, the electronic speed controller, the DC brushless motor, and the rotor / propeller.

[0006] According to an embodiment of this application, a method for determining risk sources of a distributed electric aircraft based on flight profiles is provided. The multiple phases include vertical takeoff, climb, mode transition, cruise, glide, and vertical landing. The typical operating conditions for vertical takeoff and climb are uniform acceleration ascent; the typical operating condition for mode transition is the change of horizontal propeller throttle in the transition mode; the typical operating conditions for the cruise phase include at least dynamic changes in hover load, cruise endurance analysis, battery pack failure degradation, and single-power failure; the typical operating conditions for glide and vertical landing are uniform acceleration descent.

[0007] According to an embodiment of this application, a method for determining risk sources of a distributed electric aircraft based on flight profiles is provided. The method further includes: constructing a mathematical model of the high-power-density battery pack based on the relationship between load current and output voltage; constructing a mathematical model of the DC-DC buck converter based on the linear relationship between input voltage, duty cycle, and output voltage; constructing a mathematical model of the electronic speed governor based on the coupling relationship between the input throttle signal and the output voltage of the battery pack; constructing a mathematical model of the brushless DC motor based on the equivalent relationship between the propeller speed and torque and the motor output speed and torque; and constructing a mathematical model of the rotor / propeller based on the relationship between the aerodynamic model of the blade cross-section and the overall performance of the blade.

[0008] According to the embodiment of this application, a method for determining the risk sources of a distributed electric aircraft based on flight profiles is provided. The mathematical model of the high-power-density battery pack is: Calculation formula (1): ; Calculation formula (2): ;in, This indicates the output terminal voltage; This indicates the open-circuit voltage of the battery pack; This represents the load current; Indicates the internal resistance of the ohm; Indicates polarization voltage; Indicates polarization capacitance; Indicates polarization resistance; This represents a continuous time variable during the simulation process.

[0009] According to the embodiment of this application, a method for determining the risk sources of a distributed electric aircraft based on flight profiles is provided. The mathematical model of the DC-DC step-down converter is: Calculation formula (3): ; Calculation formula (4): ;in, Indicates DC voltage gain; This indicates the duty cycle; This indicates the stable value of the output voltage; This represents the stable value of the input voltage; This indicates the stable value of the output current; Indicates conversion efficiency; This indicates the stable value of the input current.

[0010] According to the embodiment of this application, a method for determining the risk sources of a distributed electric aircraft based on flight profiles is provided. The mathematical model of the electronic speed controller is: Calculation formula (5): ; Calculation formula (6): Calculation formula (7): ; Calculation formula (8): ; Calculation formula (9): ; Calculation formula (10): ; Calculation formula (11): ; Calculation formula (12): ; Calculation formula (13): ;in, This indicates the input voltage of the electronic speed controller; This indicates the output voltage of the battery pack; This indicates the output current of the battery pack; This represents the equivalent internal resistance of the battery pack; This represents the equivalent DC voltage after electronic modulation. Indicates the equivalent voltage of the motor; Indicates the motor current; This represents the equivalent internal resistance of the electronic speed controller; This indicates the input throttle signal; This indicates the input current of the electronic speed controller; Indicates the correction factor; , , and Represents the fitting coefficient; Represents the natural constant; Indicates the number of rotors of the aircraft; This represents the sum of the operating currents required by all components other than the rotor / propeller; Indicates the maximum input current; This indicates the maximum output current of the battery pack.

[0011] According to the embodiment of this application, a method for determining the risk sources of a distributed electric aircraft based on flight profiles is provided. The mathematical model of the brushless DC motor is: Calculation formula (14): ; Calculation formula (15): ; Calculation formula (16): ;in, Indicates the equivalent voltage of the motor; Indicates the motor current; Indicates the internal resistance of the motor; Indicates a controlled voltage source; This represents the characteristic constant of the first motor; This indicates the rotational speed of the propeller; This indicates the torque of the propeller; This represents the characteristic constant of the second motor; This indicates a controlled current source.

[0012] According to the embodiment of this application, a method for determining the risk sources of a distributed electric aircraft based on flight profiles is provided, wherein the mathematical model of the rotor / propeller is: calculation formula (17): ; Calculation formula (18): ; Calculation formula (19): ; Calculation formula (20): ; Calculation formula (21): ;in, This indicates the thrust of the rotor / propeller; This indicates the thrust coefficient of the propeller; Indicates air density; This indicates the rotational speed of the propeller; This indicates the diameter of the propeller; This indicates the torque of the rotor / propeller; This represents the torque coefficient of the propeller; Indicates the forward ratio; This represents the free flow velocity perpendicular to the plane of the propeller disk; , and This represents the fitting coefficient of the tensile force coefficient; , and The fitting coefficient represents the torque coefficient.

[0013] This application also provides a distributed electric aircraft risk source determination system based on flight profiles, including: The acquisition module is used to acquire the flight profile and topology of the distributed electric aircraft, and to acquire the typical operating conditions of each stage in the multiple stages corresponding to the flight profile and the overall construction content corresponding to the topology. The overall construction content includes a high power density battery pack, a DC-DC buck converter, an electronic speed controller, a DC brushless motor, and a rotor / propeller. The simulation module is used to simulate the mathematical models of the high power density battery pack, the DC-DC buck converter, the electronic speed controller, the DC brushless motor, and the rotor / propeller under the target typical operating conditions of the target stage, and to obtain the simulation results corresponding to the target typical operating conditions. The target stage is any one of the multiple stages. The processing module is used to determine the flight test risk sources of the distributed electric aircraft under the target typical operating conditions from the high power density battery pack, the DC buck converter, the electronic speed controller, the DC brushless motor, and the rotor / propeller, based on the simulation results corresponding to the target typical operating conditions.

[0014] This application 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 risk source determination method for distributed electric aircraft based on flight profiles as described above.

[0015] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for determining risk sources of distributed electric aircraft based on flight profiles as described above.

[0016] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method for determining risk sources of distributed electric aircraft based on flight profiles as described above.

[0017] The method and system for determining risk sources of distributed electric aircraft based on flight profiles provided in this application embodiment obtain the flight profile and topology of the distributed electric aircraft, and obtain the typical operating conditions of each stage in multiple stages corresponding to the flight profile and the overall construction content corresponding to the topology. The overall construction content includes a high-power density battery pack, a DC-DC buck converter, an electronic speed controller, a brushless DC motor, and a rotor / propeller. Under the target typical operating conditions of the target stage, the mathematical models of the high-power density battery pack, the DC-DC buck converter, the electronic speed controller, the brushless DC motor, and the rotor / propeller are simulated to obtain the simulation results corresponding to the target typical operating conditions. The target stage is any one of the multiple stages. Based on the simulation results corresponding to the target typical operating conditions, the flight test risk sources of the distributed electric aircraft under the target typical operating conditions are determined from the high-power density battery pack, the DC-DC buck converter, the electronic speed controller, the brushless DC motor, and the rotor / propeller. This method addresses the complex electromechanical coupling characteristics of distributed electric aircraft by constructing a mathematical model of the overall structure of the distributed electric aircraft and conducting in-depth simulations of typical operating conditions across the entire flight profile. This accurately identifies the risk sources for flight testing of distributed electric aircraft under specific typical operating conditions, significantly reducing the flight risk of new aircraft configurations (i.e., distributed electric aircraft), improving flight test efficiency, and ultimately achieving quantitative performance evaluation throughout the entire life cycle. It can provide detailed and multi-dimensional data support for determining safety boundaries and obtaining airworthiness certification under complex operating conditions, making up for the shortcomings of existing methods such as insufficient verification, high R&D costs, and lack of data accumulation. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in 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, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the method for determining risk sources of distributed electric aircraft based on flight profiles provided in this application embodiment; Figure 2 This is a schematic diagram of a typical flight profile of the compound-wing UAV provided in the embodiments of this application; Figure 3 This is a schematic diagram of the first-order equivalent circuit model of the high power density battery pack provided in the embodiments of this application; Figure 4 This is a schematic diagram of the circuit principle of the DC-DC buck converter provided in the embodiments of this application; Figure 5This is a schematic diagram of the input-output relationship of the Buck converter provided in the embodiments of this application; Figure 6 This is a schematic diagram of the voltage control switch model provided in the embodiments of this application; Figure 7 The duty cycle provided in the embodiments of this application With correction factor A diagram illustrating the correspondence between them; Figure 8 This is a schematic diagram showing the relationship between the input voltage of the motor and the input throttle signal provided in an embodiment of this application; Figure 9 This is a schematic diagram of the equivalent circuit model of the brushless DC motor provided in the embodiments of this application; Figure 10 This is a schematic diagram of the force analysis of leaf elements provided in the embodiments of this application; Figure 11 This is a schematic diagram illustrating the relationship between the tension coefficient and torque coefficient and the advance ratio provided in the embodiments of this application; Figure 12 This is a schematic diagram illustrating the changes in motor speed and torque during the vertical takeoff and climb processes provided in the embodiments of this application; Figure 13 This is a schematic diagram of the structure of the distributed electric aircraft risk source determination system based on flight profile provided in the embodiments of this application; Figure 14 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] It should be noted that the execution entity involved in the embodiments of this application can be a distributed electric aircraft risk source determination system based on flight profiles, or it can be an electronic device. Optionally, the electronic device may include: a computer / laptop, a mobile terminal, a server, an aircraft central control device, etc.

[0022] The following section uses electronic devices as an example to illustrate in detail the method for determining risk sources of distributed electric aircraft based on flight profiles provided in this application: Figure 1 This is a flowchart illustrating the method for determining risk sources of distributed electric aircraft based on flight profiles, provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps 101-104.

[0023] Step 101: Obtain the flight profile and topology of the distributed electric aircraft, and obtain the typical operating conditions of each stage in the multiple stages corresponding to the flight profile and the overall construction content corresponding to the topology. The overall construction content includes a high power density battery pack, a DC-DC buck converter, an electronic speed controller, a DC brushless motor, and rotors / propellers.

[0024] Distributed electric aircraft refers to aircraft that employs distributed electric propulsion technology. Its core feature is the distribution of multiple electrically driven propulsion units (such as multiple rotors, propellers, or ducted fans) across the aircraft's fuselage. Optionally, distributed electric aircraft may include at least compound-wing unmanned aerial vehicles (UAVs) and eVTOLs.

[0025] In step 101, the electronic equipment can first construct a flight profile (such as...) based on the commonly used vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) configurations and the characteristics of UAV usage in distributed electric aircraft. Figure 2 The flight profile shown is a typical flight profile of a compound-wing UAV. This flight profile includes multiple stages, which may optionally include at least vertical takeoff (the process of leaving the ground and ascending to a safe altitude), climb (the process of ascending from a safe altitude to the target cruising altitude), mode transition, cruise, glide, and vertical landing.

[0026] Then, the electronic device acquires the typical operating conditions of each of the above multiple stages. Optionally, the typical operating condition for vertical takeoff and climb is uniform acceleration ascent; the typical operating condition for mode transition is the change of horizontal propeller throttle in the transition mode; the typical operating conditions for cruise stage include at least the dynamic change of hover load, cruise condition endurance analysis, battery pack failure degradation and single power failure, etc.; the typical operating condition for glide and vertical landing is uniform acceleration descent.

[0027] While acquiring the flight profile, the electronic device can construct a topology based on the characteristics of the distributed electric aircraft. Optionally, this topology may include at least an energy system, an electric drive system, and a propulsion system. The energy system may include at least high-power-density battery packs such as solid-state batteries and lithium batteries; the electric drive system may include at least a DC-DC buck converter, an electronic speed controller, a rotor motor, and a propulsion motor; and the propulsion system may include at least a rotor / propeller.

[0028] Finally, based on the above topology, the electronic device analyzes the overall system construction content. Optionally, the overall construction content may include at least a high power density battery pack, a DC-DC buck converter, an electronic speed controller, a DC brushless motor (corresponding to the rotor motor and propulsion motor mentioned above), and rotor / propeller, etc.

[0029] Optionally, the configuration of a vertical takeoff and landing unmanned aircraft may include at least a compound wing configuration, a tiltrotor / tilt wing configuration, a multi-rotor configuration, and a ducted fan configuration.

[0030] Optionally, the characteristics of aircraft use may include at least the following: limited take-off and landing sites, mode switching requirements, high power burst characteristics, and low-altitude multi-condition operation.

[0031] Optionally, the characteristics of the aircraft itself may include at least the strong coupling of electromechanical multi-physics fields caused by the distributed layout, the high power redundancy safety requirements, lightweight structural constraints, and aerodynamic nonlinear characteristics under cross-modal operation.

[0032] To better understand the multiple stages and their typical operating conditions, examples of each typical operating condition are provided in Table 1. In Table 1, the distributed electric aircraft is referred to as an unmanned aerial vehicle (UAV).

[0033] Table 1: It should be noted that the timing of the electronic device acquiring flight profiles and topology is not limited; the timing of the electronic device acquiring typical operating conditions and overall construction content is also not limited.

[0034] Optionally, after step 101, the method may further include: constructing a mathematical model of the overall construction content of the electronic device.

[0035] In some embodiments, the electronic device constructs a mathematical model of the overall structure, which may include: the electronic device constructing a mathematical model of a high-power-density battery pack based on the relationship between load current and output voltage; the electronic device constructing a mathematical model of a DC-DC buck converter based on the linear relationship between input voltage, duty cycle, and output voltage; the electronic device constructing a mathematical model of an electronic speed governor based on the coupling relationship between the input throttle signal and the output voltage of the battery pack (i.e., the aforementioned high-power-density battery pack); the electronic device constructing a mathematical model of a DC brushless motor based on the equivalent relationship between the propeller speed and torque and the motor output speed and torque; and the electronic device constructing a mathematical model of a rotor / propeller based on the relationship between the aerodynamic model of the blade cross-section and the overall performance of the blade.

[0036] It should be noted that the mathematical model of the overall structure described above ensures both computational efficiency and physical accuracy, and can be used for subsequent simulations of typical operating conditions. Specifically: For high-power-density battery packs: An equivalent circuit model (ECM) is used to reflect the battery's electrical characteristics, and the recursive forgetting factor least squares (RFF-LS) method is employed to identify the ECM parameters. To better accommodate the polarization processes with different time constants for electrochemical and concentration polarization, a first-order equivalent circuit model for the high-power-density battery pack is established, such as... Figure 3 As shown.

[0037] In some embodiments, combined with Figure 3 The mathematical model for high power density battery packs is as follows: Calculation formula (1): ; Calculation formula (2): ; in, Indicates the output voltage; Indicates the open-circuit voltage of the battery pack; Indicates the load current; Indicates the internal resistance of the ohm; Indicates polarization voltage; Indicates polarization capacitance; Indicates polarization resistance; This represents a continuous time variable during the simulation process.

[0038] For DC-DC buck converters: A high-input, low-output converter (such as a Buck converter) is employed. A mathematical model of this DC-DC buck converter is established based on the voltage-current balance under continuous conduction mode (CCM), deriving the linear relationship between input voltage, duty cycle, and output voltage. The circuit schematic of this DC-DC buck converter is shown below. Figure 4 As shown.

[0039] In some embodiments, combined with Figure 4 The mathematical model of the DC-DC buck converter is: Calculation formula (3): ; Calculation formula (4): ; in, Indicates the DC voltage gain in continuous conduction mode; This represents the duty cycle, which is the ratio of the switch's on time to the switch cycle. This indicates the stable value of the output voltage; This indicates the stable value of the input voltage; This indicates the stable value of the output current; Indicates conversion efficiency; This indicates the stable value of the input current.

[0040] It should be noted that, because the Buck converter has 0 < With a duty cycle of less than 1, this Buck converter can perform effective buck conversion. By adjusting the duty cycle... This allows for precise control of the motor armature voltage, thereby affecting the motor's speed. Generally speaking, the duty cycle... The larger the voltage, the higher the average voltage output to the motor, and the faster the motor speed.

[0041] For example, setting the input voltage 44.4V, input current It is 50A, and the conversion efficiency is... The duty cycle is 90. By increasing linearly, the input-output relationship of the Buck converter can be obtained as follows: Figure 5 As shown. From Figure 5 It can be seen from this that: as the duty cycle... The increase in output voltage Gradually increase, while the output current It decreased inversely.

[0042] For electronic speed governors: the electronic speed governor is equivalent to a voltage-controlled switch model, which controls the input throttle signal (duty cycle). The coupling relationship between the input current and output voltage of the electronic speed controller and the battery pack was investigated, and a mathematical model was established relating the input current, output voltage, and mechanical load of the electronic speed controller. The voltage control switch model is as follows: Figure 6 As shown.

[0043] In some embodiments, combined with Figure 6 The mathematical model of the electronic speed controller is: Calculation formula (5): ; Calculation formula (6): Calculation formula (7): ; Calculation formula (8): ; Calculation formula (9): ; Calculation formula (10): ; Calculation formula (11): ; Calculation formula (12): ; Calculation formula (13): ; in, Indicates the input voltage of the electronic speed controller; This indicates the output voltage of the battery pack; This indicates the output current of the battery pack; This represents the equivalent internal resistance of the battery pack. This represents the equivalent DC voltage after electronic modulation. Indicates the equivalent voltage of the motor; Indicates the motor current; This represents the equivalent internal resistance of the electronic speed controller; It indicates the input throttle signal and also the duty cycle; This indicates the input current of the electronic speed controller; Indicates the correction factor; , , and Represents the fitting coefficient; Represents the natural constant; Indicates the number of rotors of an aircraft; This represents the sum of the operating current required by all components other than the rotor / propeller; Indicates the maximum input current; This indicates the maximum output current of the battery pack.

[0044] It should be noted that, due to the equivalent internal resistance of the battery pack The value is very small; therefore, without considering the equivalent internal resistance of the line... Under the conditions of voltage division and voltage loss at the interface, the output voltage of the electronic speed controller With the output voltage of the battery pack They can be approximated as equal, combined with Figure 6 Thus, the above calculation formulas (6) and (7) can be obtained.

[0045] Without considering the power loss caused by the heat generated by the electronic speed controller, the input and output power of the electronic speed controller are theoretically the same, so the above calculation formula (8) can be obtained.

[0046] A correction factor is introduced to account for power loss caused by heat generation in the electronic speed controller. This is used to determine the effect of the throttle signal on the input current of the electronic speed governor. Under low input throttle signals, the efficiency of the electronic speed governor exhibits an exponential increase. While the efficiency tends to stabilize under medium to high input throttle signals, the calculations related to the motor previously neglected mechanical losses, resulting in a larger error in the calculated value at this point. Therefore, a correction factor that varies with the throttle signal is introduced to consider both factors. By correcting the calculation of the input current of the electronic speed controller in the above calculation formula (8), the above calculation formula (9) can be obtained.

[0047] Generally speaking, when the duty cycle When it is small, the correction factor The smaller the duty cycle, the higher the duty cycle. The larger the value, the greater the correction factor. Close to 1, duty cycle With correction factor The correspondence between them can be represented by an exponential function, the calculation formula of which is the above calculation formula (10). Wherein, duty cycle... With correction factor The correspondence between them is as follows: Figure 7 As shown.

[0048] For multi-rotor drones, the battery pack not only supplies power to the power system, but also provides energy to all other components (such as flight control, Global Positioning System (GPS) components, aerial cameras and signal receiving devices, etc.). The discharge current of the battery pack (i.e. the output current of the battery pack) is calculated by the above calculation formula (11).

[0049] Due to the maximum output current of the battery pack Due to limitations, the input current of the electronic speed controller... With maximum input current The above calculation formula (12) should be satisfied.

[0050] For example, the input voltage of the electronic speed controller is set. The input current of the electronic speed controller is 44.4V. The equivalent internal resistance of the electronic speed controller is 100A. The resistance is 0.001Ω. The relationship between the motor's input voltage (i.e., the motor's equivalent voltage) and the input throttle signal is as follows: Figure 8 The convex curve shown. From Figure 8 It can be seen from this that: in the equivalent internal resistance of the electronic speed controller In cases where the voltage is low, energy loss is not significant, and the motor's input voltage changes approximately linearly with the throttle position.

[0051] For brushless DC motors: Both rotor motors and propulsion motors can be modeled using brushless DC motors. An equivalent circuit model is used to model this brushless DC motor. For the dynamics of this brushless DC motor, to facilitate integration with the battery pack, electronic speed controller, and propeller models, and to simplify parameters and improve simulation efficiency while maintaining accuracy, a simplified brushless DC motor model can be used for simulation analysis. The equivalent circuit model of this brushless DC motor is as follows: Figure 9As shown. In Figure 9 In this case, the angular acceleration of the motor is ignored, meaning that the propeller's speed and torque are always equal to the motor's output speed and torque.

[0052] In some embodiments, combined with Figure 9 The mathematical model of a brushless DC motor is: Calculation formula (14): ; Calculation formula (15): ; Calculation formula (16): ; in, Indicates the equivalent voltage of the motor; Indicates the motor current; Indicates the internal resistance of the motor; Indicates a controlled voltage source; This represents the characteristic constant of the first motor; Indicates the rotational speed of the propeller; Indicates the torque of the propeller; This represents the characteristic constant of the second motor; This indicates a controlled current source.

[0053] For rotors / propellers: vortex theory is used to model the rotors / propellers. Thrust is calculated. Torque And efficiency parameters, to achieve a consistent description of aerodynamic performance and power output.

[0054] Figure 10 This is a schematic diagram of the force analysis of leaf elements provided in an embodiment of this application. From Figure 10 As can be seen, the input to eddy current theory is the aerodynamic model of the blade cross-section (blade element). Among them, Indicates the rotational speed of the propeller; Indicates the speed of movement through the air; The aerodynamic twist angle of the blade element is the angle between the zero-lift line of the blade element and the descending disk plane. The zero-lift line of the blade element varies with the radius. It changes with the changes; This represents the total aerodynamic force on the leaf element; This indicates the lift of the leaf element; Indicates the resistance of folin, Indicates the apnea angle of leaf element; Indicates the tensile strength of the leaf element; This represents the tangential force of the leaf element.

[0055] Angle of attack of leaf element The calculation formula is: ;in, This indicates the total downwash angle.

[0056] Downwash angle The calculation formula is: ;in, Indicates the angle of advance; Indicates the interference angle.

[0057] rate of leaf element synthesis Including free flow velocity and induction speed Tangential induced velocity and rotational speed The rate of leaf nutrient synthesis The calculation formula is: .

[0058] Lift of leaf extract It is the rate of leaf element synthesis. The function, whose expression is: ; resistance of folin It is the rate of phytochemical synthesis. The function, whose expression is: .in, Indicates air density; Indicates the lift coefficient. The drag coefficient is determined by the Reynolds number of the leaf element. ,Mach number and aerodynamic angle of attack ; This indicates the chord length of the blade element (or the chord length of the propeller / rotor blade).

[0059] For the number of blades The propeller, the thrust of the blade element The calculation formula is: .

[0060] Leaf element torque The calculation formula is: .

[0061] Based on the Kutta-Joukowski theorem, the circulation of the section about the lift force is explained. The generated lift The calculation formula is: .

[0062] According to eddy current theory, induced velocity It can be predicted under two assumptions that satisfy the Betz condition: first, that the propeller wake is attached to a helical surface with a constant pitch; second, that the induced velocity... perpendicular to the resultant velocity At this point, the induction velocity and tangential induced velocity The following relationship must be satisfied: Therefore, we can deduce that: .

[0063] In eddy current theory, tangential induced velocity is... The amount of attachment ring with foliol Connecting them together, we get: .

[0064] Kappa factor The geometric meaning is clear, but it is difficult to obtain an exact value. An approximate solution can be obtained using the Prandtl tip loss coefficient. Specifically, it means: .in, Indicates the diameter of the propeller; Indicates the propeller tip installation angle.

[0065] Using all the formulas corresponding to leaf elements, the interference angle can be calculated. Then the thrust of the propeller can be calculated. and torque Based on this, the thrust of the rotor / propeller By adjusting the thrust Along the root of the paddle To the tip of the paddle The result is obtained through integration, specifically: Rotor / propeller torque By measuring torque Along the root of the paddle To the tip of the paddle The result is obtained through integration, specifically: .

[0066] Specifically: the thrust coefficient of a fixed-wing propeller The calculation formula is: .

[0067] Torque coefficient of fixed-wing propeller The calculation formula is: .

[0068] Power coefficient of fixed-wing propeller The calculation formula is: .

[0069] Efficiency of fixed-wing propellers The calculation formula is: .

[0070] in, Indicates the thrust of the propeller; Indicates the diameter of the propeller; This indicates the rotational angular velocity of the propeller; Indicates the torque of the propeller; This indicates the propeller's advance ratio. ; Indicates the thrust coefficient of the propeller; This indicates the power coefficient of the propeller.

[0071] Rotor thrust coefficient The calculation formula is: .

[0072] rotor torque coefficient The calculation formula is: .

[0073] rotor power coefficient The calculation formula is: .

[0074] rotor efficiency The calculation formula is: .

[0075] in, Indicates the thrust of the rotor; Indicates the area of ​​the rotor disk; This indicates the angular velocity of the rotor. Indicates the radius of the rotor; This indicates the rotor torque.

[0076] In some embodiments, combined with Figure 10 Based on the above formula, the mathematical model for the rotor / propeller is: Calculation formula (17): ; Calculation formula (18): ; Calculation formula (19): ; Calculation formula (20): ; Calculation formula (21): ; in, Indicates the thrust of the rotor / propeller; Indicates the thrust coefficient of the propeller; Indicates air density; This indicates the rotational speed of the propeller (in r / min). Indicates the diameter of the propeller; Indicates the torque of the rotor / propeller; This indicates the torque coefficient of the propeller; Indicates the forward ratio; This represents the free flow velocity perpendicular to the plane of the propeller disk; , and The fitting coefficient represents the tensile strength coefficient; , and This represents the fitting coefficient for the torque coefficient.

[0077] Obviously, thrust With torque Both are rotational speeds A quadratic function.

[0078] It should be noted that in dynamic thrust state, the incoming flow velocity will change the angle of attack of the propeller blades, and the effect of different combinations of rotational speed and incoming flow velocity on the angle of attack is different. The same incoming flow velocity may have little effect on high-speed propellers, but may significantly reduce the thrust of low-speed propellers. Therefore, the concept of the ratio of incoming flow velocity to blade tip linear velocity is proposed, called the advance ratio, which can be calculated by the above calculation formula (19).

[0079] According to the strip theory, the tensile coefficient and torque coefficient Compared with progress It satisfies the polynomial relationship, namely the above calculation formula (20) and calculation formula (21).

[0080] For example, Figure 11 This is a schematic diagram illustrating the relationship between the tension coefficient, torque coefficient, and advance ratio provided in an embodiment of this application. Figure 11 It can be seen that the tension coefficient and torque coefficient decrease as the forward ratio increases.

[0081] Step 102: Under the target typical operating conditions of the target stage, simulate the mathematical models of the high power density battery pack, DC buck converter, electronic speed controller, DC brushless motor and rotor / propeller respectively, and obtain the simulation results corresponding to the target typical operating conditions. The target stage can be any one of multiple stages.

[0082] In step 102, the electronic equipment can simulate the mathematical models of the high power density battery pack, DC-DC buck converter, electronic speed controller, DC brushless motor and rotor / propeller under typical operating conditions in each of the multiple stages, and obtain the simulation results corresponding to each typical operating condition to guide flight verification.

[0083] It should be noted that the simulation results corresponding to the target typical operating conditions may include at least the first simulation results corresponding to the high power density battery pack, the second simulation results corresponding to the DC buck converter, the third simulation results corresponding to the electronic speed controller, the fourth simulation results corresponding to the DC brushless motor, and the fifth simulation results corresponding to the rotor / propeller.

[0084] Optionally, the first simulation results may include at least the risks of current overrun, voltage sag, and thermal runaway.

[0085] Optionally, the second simulation results may include at least voltage ripple exceeding the limit, thermal overload drop, and rated conversion efficiency drop.

[0086] Optionally, the third simulation results may include at least transient overcurrent, commutation failure (loss of synchronization), and control saturation risk.

[0087] Optionally, the fourth simulation results may include at least the risks of winding overheating, torque / current nonlinear instability, and mechanical vibration.

[0088] Optionally, the fifth simulation results may include at least blade stall risk, tip Mach number exceeding limits, and vortex ring status.

[0089] For example, the simulation results are analyzed using the uniform acceleration ascent condition during the vertical takeoff and climb phases. This uniform acceleration ascent condition uses an ambient temperature of 25°C and an initial battery pack temperature of 25°C as initial conditions, based on... Figure 12 The diagram illustrates the changes in motor speed and torque during vertical takeoff and climb. During both phases, the torque (control variable) rapidly increases to establish propeller disk angular momentum, causing the speed to rise and stabilize at approximately 2600 rpm within 3-10 seconds. At this point, the electronic equipment primarily converts electrical energy into two parts: maintaining rotor kinetic energy and mitigating frictional losses, and using power to counteract gravity. After reaching the target altitude in approximately 28 seconds, the speed command switches from "ascending" to "zero vertical speed," instantly dropping the climb power requirement to near zero, requiring only hover thrust. Therefore, the electronic equipment can quickly reduce torque, resulting in a significant decrease. However, due to the equivalent rotational inertia of the rotor / motor, the short-term "stock" of angular momentum makes speed fluctuations weaker than torque fluctuations. Subsequently, the electronic equipment increases torque for tracking and readjustment, completing the speed overshoot-regression-convergence process. Overall, the rotational speed is a passive result of torque control under the "step decrease in power demand": torque directly undertakes power redistribution (switching from "climb power + sustaining power" to "sustaining power"), so the transient amplitude of this torque is larger; while the rotational speed is filtered by rotational inertia and electrical time constant, resulting in smaller fluctuations. The entire vertical takeoff and climb process demonstrates the rationality of energy channel switching and control damping: power peaks are limited to a short period of time, and a smooth transition to hovering power is finally completed after about 32 seconds.

[0090] Simulation results for the uniform acceleration ascent during vertical takeoff and climb phases show that the rotational speed undergoes an overshoot-retreat-convergence process during the mode transition from vertical takeoff and climb to cruise. Actual UAVs experience altitude loss. To mitigate this adverse effect, the climb phase can be subdivided into three stages during actual flight tests: uniform acceleration vertical takeoff, uniform speed vertical takeoff, and uniform deceleration vertical takeoff. This ensures a smooth and seamless transition between the rate of vertical lift decay and the rate of horizontal lift increase. Alternatively, some thrusters (behind the wings) can be kept vertical or at a small angle during operation to provide lift compensation during the transition phase, then deactivated or converted to cruise thrust after the transition is complete.

[0091] Taking the horizontal propeller throttle variation during the mode transition phase as an example, the simulation results are analyzed. During the mode transition phase, the core logic of the electronic equipment lies in achieving a smooth transfer of lift weight. As the UAV transitions from vertical climb to horizontal acceleration, the throttle signal of the horizontal propeller begins to gradually increase from zero, either stepwise or linearly. During this process, the horizontal propeller's rotational speed rapidly responds to the throttle command, generating horizontal thrust to overcome fuselage drag and establish forward speed.

[0092] Simulation results corresponding to the horizontal propeller throttle variation during the mode transition phase show that the horizontal propeller torque has a significant peak at startup, which is used to overcome static friction and rotor inertia. As the advance ratio is established, the wing begins to generate aerodynamic lift. At this time, the electronic equipment coordinates to reduce the vertical rotor throttle, causing the vertical thrust to gradually decrease.

[0093] It should be noted that, in order to suppress the "loss of altitude" phenomenon, the electronic equipment maintains the horizontal propeller throttle at a high gain during the transition phase, ensuring that the rate of increase in horizontal lift can fully compensate for the shortfall in vertical lift. At this time, the adjustment of the horizontal throttle exhibits a step-by-step increase—local fine-tuning—convergence characteristic, and finally, after reaching the cruising speed, the throttle stabilizes at the balance point that maintains the ability to overcome cruising drag.

[0094] Taking a typical cruise phase as an example, the simulation results are analyzed. For the dynamic change of hovering load: when subjected to environmental gusts or load center of gravity shift, the electronic equipment adjusts the differential torque of each rotor in real time through a feedback loop. Simulation results show that the torque curve exhibits high-frequency but small-amplitude oscillations to generate a corrective torque, while the rotational speed, filtered by rotational inertia, exhibits low-frequency smooth fluctuations, ensuring that the steady-state error of the hovering height is controlled within a minimal range.

[0095] For the cruise endurance analysis: As the flight mission continues, the battery pack's output voltage gradually decreases due to increased depth of discharge. To maintain power balance, the electronic equipment automatically compensates for the throttle duty cycle, causing the current to rise slowly to offset the voltage drop. Simulation results reveal a slight decrease in energy efficiency as heat generation from battery internal resistance increases.

[0096] For battery pack failure degradation scenarios: When a partial cell failure or overheating occurs in the simulated battery pack, the electronic equipment immediately triggers a degradation strategy, limiting the maximum output current within a safe threshold. At this time, the propeller throttle is forcibly locked at a low position, and the UAV switches from high-speed cruise to economical flight speed, significantly reducing the power spectral density and prioritizing the power supply security of the core avionics system.

[0097] For single-power failure (power redundancy) scenarios: Under the extreme condition of simulating the failure of a single motor, the electronic equipment utilizes a redundancy control algorithm to rapidly increase the torque output of the remaining healthy motors. As can be seen in the simulation diagram, the torque on the corresponding axis drops to zero instantly at the moment of failure, while the speed of the opposite and adjacent motors increases sharply. By sacrificing some cruise efficiency in exchange for attitude trim of the flight platform, the system ultimately achieves either flight with the fault or controlled return to base.

[0098] Taking the uniform acceleration descent conditions of glide and vertical landing as examples, the simulation results are analyzed. The uniform acceleration descent condition is the reverse process of vertical takeoff, and the key lies in the precise control of potential energy release and gravity balance.

[0099] During the initial descent phase, the electronic equipment actively reduces the rotor throttle to make the total thrust slightly less than gravity, allowing the UAV to enter a uniform acceleration descent state. At this time, due to the influence of the rotor's "autorotation" or "vortex ring" edge effect, the torque fluctuation is relatively violent, and the electronic equipment needs to use high-frequency closed-loop adjustment to suppress the attitude sway caused by airflow disturbance.

[0100] As the drone approaches the target altitude, the speed command switches to uniform deceleration mode. The electronic systems quickly compensate for the torque, increasing power output to generate "reverse thrust" for braking. Simulation results show that in the final 5 seconds before landing, the rotational speed undergoes a significant increase to counteract the descent inertia. Finally, around 30-35 seconds, thrust and gravity reach equilibrium again, and the drone lands smoothly with an extremely low touchdown speed. The entire process demonstrates the high dynamic response characteristics of the control system under varying drag conditions.

[0101] Step 103: Based on the simulation results corresponding to the target typical operating conditions, identify the risk sources for flight testing of the distributed electric aircraft under the target typical operating conditions from the high power density battery pack, DC buck converter, electronic speed controller, DC brushless motor and rotor / propeller.

[0102] In step 103, the electronic device can obtain flight test risk sources based on the simulation results. Specifically, the electronic device analyzes the first simulation results corresponding to the high power density battery pack, the second simulation results corresponding to the DC buck converter, the third simulation results corresponding to the electronic speed controller, the fourth simulation results corresponding to the DC brushless motor, and the fifth simulation results corresponding to the rotor / propeller. The components corresponding to the target simulation results that do not meet the preset conditions among the five simulation results are taken as the flight test risk sources of the distributed electric aircraft under the target typical operating conditions.

[0103] For example, assuming that the second, third, fourth, and fifth simulation results are all within the safe range, while the data in the first simulation result is not within the safe range, then battery fault degradation (short circuit, open circuit, overheating discharge fault), single power failure (single battery failure, single motor ESC failure), and other faults are obtained, and the high power density battery pack is regarded as the risk source of flight test.

[0104] Optionally, after step 103, the method may further include: the electronic device formulating corresponding risk mitigation measures based on the risk sources of the flight test.

[0105] For example, taking a single power failure as an example, the causes of failure include the failure of a single battery power supply, the failure of a single motor due to overheating or overload, the failure of a single electronic speed controller due to electromagnetic interference, and the temperature of any battery pack exceeding the warning value. The risks brought about by a single power failure include the loss of a single battery pack, the risk of reduced power and shortened range; the absence of the single motor and electronic speed controller will immediately change the torque balance and aerodynamic environment of the aircraft, causing difficulties in flight control operation.

[0106] Risk control measures: Regarding single-battery power failure, if the UAV's electric propulsion system has redundancy, the backup battery will be activated, and the flight mission will continue once the power is restored. If not, the pilot must assess the battery capacity based on the flight path and select the nearest landing point. For single-unit or ESC failures, the UAV's flight control system will be adjusted to maintain flight. If the adjustments are ineffective, a forced gliding landing will be initiated. The flight mission will be conducted on a clear, windless day to prevent turbulence from affecting flight control operations and causing secondary risks during a forced gliding landing.

[0107] Optionally, the method may further include: electronic devices, based on risk mitigation measures and in conjunction with flight profiles, assisting in flight verification and reducing flight risks.

[0108] For example, to mitigate the high power risk during vertical takeoff, a joint current-temperature limiting algorithm is activated. This algorithm works when the battery pack's discharge rate approaches the simulated maximum output current. If the electronic speed controller heats up too quickly, the electronic equipment does not directly cut off the power, but instead maintains the power at the edge of the safety envelope by finely adjusting the rate of increase command. Verification assistance involves real-time comparison of the actual speed with the convergence curve predicted by the simulation; if the deviation exceeds 5%, the control damping is automatically increased.

[0109] To mitigate the risk of lift instability during mode transition, the risk mitigation measure is to implement "lift compensation and logic interlocking". When the horizontal propeller throttle is raised, the electronic equipment forcibly locks the minimum lift margin of the vertical rotor to prevent "drop in altitude" due to excessively rapid transition.

[0110] To mitigate the risk of energy depletion during the cruise phase, the risk management measure is to implement range optimization based on the battery's state of charge (SoC). This is based on the equivalent internal resistance of the battery pack. The cruise speed is dynamically adjusted over time to achieve optimal conversion efficiency. flight.

[0111] To mitigate the risk of vortex ring state during the vertical descent phase, the electronic equipment incorporates a "descent rate - forward velocity" protection envelope. If abnormal fluctuations in the lift coefficient are detected due to the downwash flow field, the electronic equipment will prevent further throttle reduction and proactively increase the level flight speed or limit the vertical descent rate to force the aircraft out of the vortex ring danger zone. In the verification and assistance phase, the electronic equipment calculates the rotor inlet angle in real time and interlocks it with the stall critical point of the simulation model for monitoring.

[0112] In the embodiments of this application, the technical solutions described in steps 101-103 above target the complex electromechanical coupling characteristics of distributed electric aircraft. By constructing a mathematical model of the overall construction content of the distributed electric aircraft and conducting in-depth simulation of typical working conditions of the entire flight profile, the risk sources of flight tests of the distributed electric aircraft under specific typical working conditions are accurately determined. This significantly reduces the flight risk of the new configuration aircraft (i.e., distributed electric aircraft), improves flight test efficiency, and realizes the quantitative evaluation of performance throughout the entire life cycle. It can provide detailed and multi-dimensional data support for the determination of safety boundaries and airworthiness certification under complex working conditions, making up for the shortcomings of existing methods such as insufficient verification, high R&D costs and lack of data accumulation.

[0113] Furthermore, the aforementioned technical solution aims to construct a relatively complete mathematical model for the distributed electric aircraft. Through simulation analysis and research, it explores the key characteristics of the distributed electric aircraft, identifies flight verification hazards (i.e., flight test risk sources), and provides a solid theoretical basis and reference for the subsequent flight verification of the distributed electric aircraft and the formulation of flight control strategies. This will promote the technology of distributed electric aircraft to a higher level in practical applications and fully leverage the advantages and potential of the distributed electric aircraft in diverse scenarios.

[0114] That is to say, this technical solution can simulate multiple failure modes, and pre-design and verify corresponding risk control strategies to ensure that the UAV remains safe and controllable in case of failure, can predict the link with the highest technical risk, and provide the safest, most economical and most efficient preliminary verification approach for subsequent physical flight verification. At the same time, this technical solution can also be applied to the flight verification of low-altitude aircraft using distributed electric propulsion systems such as compound-wing UAVs and eVTOLs, can assist the above aircraft to complete relevant airworthiness clause verification, and can also assist in completing relevant scenario flight test verification.

[0115] The risk source determination system of a distributed electric aircraft based on a flight profile provided by an embodiment of the present application will be described below. The risk source determination system of a distributed electric aircraft based on a flight profile described below can be correspondingly referred to the risk source determination method of a distributed electric aircraft based on a flight profile described above.

[0116] Figure 13 It is a schematic structural diagram of the risk source determination system of a distributed electric aircraft based on a flight profile provided by an embodiment of the present application. As Figure 13 shown, the system includes: an acquisition module 1301, a simulation module 1302, and a processing module 1303.

[0117] The acquisition module 1301 is configured to acquire the flight profile and topological structure of the distributed electric aircraft, and acquire the typical working conditions of each stage in the multiple stages corresponding to the flight profile and the overall construction content corresponding to the topological structure, and the overall construction content includes a high-power density battery pack, a DC step-down converter, an electronic speed controller, a DC brushless motor, and a rotor / propeller; The simulation module 1302 is configured to simulate the mathematical models of the high-power density battery pack, the DC step-down converter, the electronic speed controller, the DC brushless motor, and the rotor / propeller respectively under the target typical working condition of the target stage, and obtain the simulation result corresponding to the target typical working condition, where the target stage is any one of the multiple stages; The processing module 1303 is configured to determine the flight test risk source of the distributed electric aircraft under the target typical working condition from the high-power density battery pack, the DC step-down converter, the electronic speed controller, the DC brushless motor, and the rotor / propeller according to the simulation result corresponding to the target typical working condition.

[0118] Optionally, the multiple phases include vertical takeoff, climb, mode transition, cruise, glide, and vertical landing; the typical operating conditions for vertical takeoff and climb are uniform acceleration ascent; the typical operating condition for mode transition is the change of horizontal propeller throttle in the transition mode; the typical operating conditions for the cruise phase include at least the dynamic changes in hover load, cruise endurance analysis, battery pack failure degradation, and single-power failure; the typical operating conditions for glide and vertical landing are uniform acceleration descent.

[0119] Optionally, the processing module 1303 is further configured to: construct a mathematical model of the high power density battery pack based on the relationship between the load current and the output voltage; construct a mathematical model of the DC-DC buck converter based on the linear relationship between the input voltage, duty cycle, and output voltage; construct a mathematical model of the electronic speed governor based on the coupling relationship between the input throttle signal and the output voltage of the battery pack; construct a mathematical model of the DC brushless motor based on the equivalent relationship between the propeller speed and torque and the motor output speed and torque; and construct a mathematical model of the rotor / propeller based on the relationship between the aerodynamic model of the blade cross-section and the overall performance of the blade.

[0120] Optionally, the mathematical model of this high power density battery pack is: Calculation formula (1): ; Calculation formula (2): ;in, This indicates the voltage at the output terminal; This indicates the open-circuit voltage of the battery pack; This indicates the load current; Indicates the internal resistance of the ohm; Indicates polarization voltage; Indicates polarization capacitance; Indicates polarization resistance; This represents a continuous time variable during the simulation process.

[0121] Optionally, the mathematical model of the DC-DC buck converter is: Calculation formula (3): ; Calculation formula (4): ;in, Indicates DC voltage gain; This indicates the duty cycle; This indicates the stable value of the output voltage; This indicates the stable value of the input voltage; This indicates the stable value of the output current; Indicates conversion efficiency; This indicates the stable value of the input current.

[0122] Optionally, the mathematical model of the electronic speed controller is: Calculation formula (5): ; Calculation formula (6): Calculation formula (7): ; Calculation formula (8): ; Calculation formula (9): ; Calculation formula (10): ; Calculation formula (11): ; Calculation formula (12): ; Calculation formula (13): ;in, This indicates the input voltage of the electronic speed controller; This indicates the output voltage of the battery pack; This indicates the output current of the battery pack; This indicates the equivalent internal resistance of the battery pack; This represents the equivalent DC voltage after electronic modulation. Indicates the equivalent voltage of the motor; Indicates the motor current; This represents the equivalent internal resistance of the electronic speed controller; This indicates the input throttle signal; This indicates the input current of the electronic speed controller; Indicates the correction factor; , , and Represents the fitting coefficient; Represents the natural constant; This indicates the number of rotors of the aircraft; This represents the sum of the operating currents required by all components other than the rotor / propeller; Indicates the maximum input current; This indicates the maximum output current of the battery pack.

[0123] Optionally, the mathematical model of the brushless DC motor is: Calculation formula (14): ; Calculation formula (15): ; Calculation formula (16): ;in, Indicates the equivalent voltage of the motor; Indicates the motor current; Indicates the internal resistance of the motor; Indicates a controlled voltage source; This represents the characteristic constant of the first motor; This indicates the rotational speed of the propeller; This indicates the torque of the propeller; This represents the characteristic constant of the second motor; This indicates a controlled current source.

[0124] Optionally, the mathematical model for the rotor / propeller is: Calculation formula (17): ; Calculation formula (18): ; Calculation formula (19): ; Calculation formula (20): ; Calculation formula (21): ;in, This indicates the thrust of the rotor / propeller; This indicates the thrust coefficient of the propeller; Indicates air density; This indicates the rotational speed of the propeller; This indicates the diameter of the propeller; This indicates the torque of the rotor / propeller; This indicates the torque coefficient of the propeller; Indicates the forward ratio; This represents the free flow velocity perpendicular to the plane of the propeller disk; , and This represents the fitting coefficient for the tensile force coefficient; , and This represents the fitting coefficient for the torque coefficient.

[0125] Figure 14 This is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. For example... Figure 14 As shown, the electronic device may include a processor 1410, a communications interface 1420, a memory 1430, and a communication bus 1440. The processor 1410, communications interface 1420, and memory 1430 communicate with each other via the communication bus 1440. The processor 1410 can call logical instructions from the memory 1430 to execute a method for determining risk sources for distributed electric aircraft based on flight profiles.

[0126] Furthermore, the logical instructions in the aforementioned memory 1430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0127] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for determining the risk source of a distributed electric aircraft based on flight profiles provided by the above methods.

[0128] In another aspect, embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the flight profile-based method for determining risk sources of distributed electric aircraft provided by the methods described above.

[0129] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0130] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for determining risk sources of distributed electric aircraft based on flight profiles, characterized in that, include: The flight profile and topology of the distributed electric aircraft are obtained, and the typical operating conditions of each stage in the multiple stages corresponding to the flight profile and the overall construction content corresponding to the topology are obtained. The overall construction content includes a high power density battery pack, a DC-DC buck converter, an electronic speed controller, a DC brushless motor, and a rotor / propeller. Under the target typical operating conditions of the target stage, the mathematical models of the high power density battery pack, the DC buck converter, the electronic speed controller, the DC brushless motor and the rotor / propeller are simulated to obtain the simulation results corresponding to the target typical operating conditions. The target stage is any one of the multiple stages. Based on the simulation results corresponding to the target typical operating conditions, the flight test risk sources of the distributed electric aircraft under the target typical operating conditions are determined from the high power density battery pack, the DC buck converter, the electronic speed controller, the DC brushless motor, and the rotor / propeller.

2. The method for determining risk sources of distributed electric aircraft based on flight profiles according to claim 1, characterized in that, The multiple phases include vertical takeoff, climb, mode transition, cruise, glide, and vertical landing; The typical operating conditions for the vertical takeoff and the climb are uniform acceleration ascent; The typical operating condition for the mode transition is the change in the throttle of the horizontal propeller in the transition mode; Typical operating conditions during the cruise phase include at least the dynamic changes in hover load, cruise endurance analysis, battery pack failure degradation, and single-power failure. The typical conditions for the descent and the vertical drop are uniform acceleration descent.

3. The method for determining risk sources of distributed electric aircraft based on flight profiles according to claim 1 or 2, characterized in that, The method further includes: A mathematical model of the high power density battery pack is constructed based on the relationship between load current and output voltage. Based on the linear relationship between input voltage, duty cycle and output voltage, a mathematical model of the DC-DC buck converter is constructed. Based on the coupling relationship between the input throttle signal and the output voltage of the battery pack, a mathematical model of the electronic speed governor is constructed. A mathematical model of the brushless DC motor is constructed based on the equivalent relationship between the propeller's rotational speed and torque and the motor's output rotational speed and torque. A mathematical model of the rotor / propeller is constructed based on the relationship between the aerodynamic model of the blade cross section and the overall performance of the blade.

4. The method for determining risk sources of distributed electric aircraft based on flight profiles according to claim 3, characterized in that, The mathematical model for the high-power-density battery pack is as follows: Calculation formula (1): ; Calculation formula (2): ; in, This indicates the output terminal voltage; This indicates the open-circuit voltage of the battery pack; This represents the load current; Indicates the internal resistance of the ohm; Indicates polarization voltage; Indicates polarization capacitance; Indicates polarization resistance; This represents a continuous time variable during the simulation process.

5. The method for determining risk sources of distributed electric aircraft based on flight profiles according to claim 3, characterized in that, The mathematical model of the DC-DC buck converter is as follows: Calculation formula (3): ; Calculation formula (4): ; in, Indicates DC voltage gain; This indicates the duty cycle; This indicates the stable value of the output voltage; This represents the stable value of the input voltage; This indicates the stable value of the output current; Indicates conversion efficiency; This indicates the stable value of the input current.

6. The method for determining risk sources of distributed electric aircraft based on flight profiles according to claim 3, characterized in that, The mathematical model of the electronic speed controller is: Calculation formula (5): ; Calculation formula (6): Calculation formula (7): ; Calculation formula (8): ; Calculation formula (9): ; Calculation formula (10): ; Calculation formula (11): ; Calculation formula (12): ; Calculation formula (13): ; in, This indicates the input voltage of the electronic speed controller; This indicates the output voltage of the battery pack; This indicates the output current of the battery pack; This represents the equivalent internal resistance of the battery pack; This represents the equivalent DC voltage after electronic modulation. Indicates the equivalent voltage of the motor; Indicates the motor current; This represents the equivalent internal resistance of the electronic speed controller; This indicates the input throttle signal; This indicates the input current of the electronic speed controller; Indicates the correction factor; , , and Represents the fitting coefficient; Represents the natural constant; Indicates the number of rotors of the aircraft; This represents the sum of the operating currents required by all components other than the rotor / propeller; Indicates the maximum input current; This indicates the maximum output current of the battery pack.

7. The method for determining risk sources of distributed electric aircraft based on flight profiles according to claim 3, characterized in that, The mathematical model of the brushless DC motor is as follows: Calculation formula (14): ; Calculation formula (15): ; Calculation formula (16): ; in, Indicates the equivalent voltage of the motor; Indicates the motor current; Indicates the internal resistance of the motor; Indicates a controlled voltage source; This represents the characteristic constant of the first motor; This indicates the rotational speed of the propeller; This indicates the torque of the propeller; This represents the characteristic constant of the second motor; This indicates a controlled current source.

8. The method for determining risk sources of distributed electric aircraft based on flight profiles according to claim 3, characterized in that, The mathematical model for the rotor / propeller is: Calculation formula (17): ; Calculation formula (18): ; Calculation formula (19): ; Calculation formula (20): ; Calculation formula (21): ; in, This indicates the thrust of the rotor / propeller; This indicates the thrust coefficient of the propeller; Indicates air density; This indicates the rotational speed of the propeller; This indicates the diameter of the propeller; This indicates the torque of the rotor / propeller; This represents the torque coefficient of the propeller; Indicates the forward ratio; This represents the free flow velocity perpendicular to the plane of the propeller disk; , and This represents the fitting coefficient of the tensile force coefficient; , and The fitting coefficient represents the torque coefficient.

9. A risk source determination system for distributed electric aircraft based on flight profiles, characterized in that, include: The acquisition module is used to acquire the flight profile and topology of the distributed electric aircraft, and to acquire the typical operating conditions of each stage in the multiple stages corresponding to the flight profile and the overall construction content corresponding to the topology. The overall construction content includes a high power density battery pack, a DC-DC buck converter, an electronic speed controller, a DC brushless motor, and a rotor / propeller. The simulation module is used to simulate the mathematical models of the high power density battery pack, the DC-DC buck converter, the electronic speed controller, the DC brushless motor, and the rotor / propeller under the target typical operating conditions of the target stage, and to obtain the simulation results corresponding to the target typical operating conditions. The target stage is any one of the multiple stages. The processing module is used to determine the flight test risk sources of the distributed electric aircraft under the target typical operating conditions from the high power density battery pack, the DC buck converter, the electronic speed controller, the DC brushless motor, and the rotor / propeller, based on the simulation results corresponding to the target typical operating conditions.

10. 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 method for determining risk sources of distributed electric aircraft based on flight profiles as described in any one of claims 1 to 8.

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