Pneumatic and operation stability collaborative design method of unmanned aerial vehicle
Through the collaborative design method of aerodynamic and handling stability of the UAV, the complex process and high resource consumption problems caused by independent design of aerodynamic and handling stability in traditional design methods are solved, and the optimal solution to the design goals and the effective utilization of resources are achieved.
Patent Information
- Application Number
- CN202411948661.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-27
- Publication Date
- 2025-05-30
AI Technical Summary
Traditional drone design methods independently carry out aerodynamic design and handling design, ignoring the mutual influence between the two, resulting in complex design processes, long iteration cycles, and large resource consumption, and the low-cost advantages of small drones are not fully utilized.
The aerodynamic and handling stability collaborative design method is adopted, and by establishing a parameterized model, optimizing the flow field grid, calculating aerodynamic data, adjusting the control system parameters, and iteratively optimized until the drone meets the maximum lift-drag ratio requirements and flight quality requirements.
The overall design process of the drone was optimized, and the aerodynamic performance, handling stability and structural strength were comprehensively considered, the optimal solution to the design goal was achieved, the design process was simplified, the iteration cycle was shortened, and the resource consumption was reduced.
Smart Images
Figure CN120057289A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of low-speed UAV aerodynamic design, and particularly to a collaborative design method for the aerodynamics and handling and stability of a UAV. Background Art
[0002] The overall design of a UAV includes the conceptual design and preliminary design stages. The conceptual design mainly determines the aerodynamic layout, power, airfoil, etc. according to the service characteristics of the UAV, and uses empirical formulas to obtain the design feasible region; in the preliminary design stage, through aerodynamic design and handling and stability simulation, the previous design parameters are iteratively optimized repeatedly. The traditional UAV design method often conducts aerodynamic design and handling and stability design independently, ignoring the mutual influence and restriction relationship between the two. In the aerodynamic design process, the influence of the aerodynamic configuration on the handling and stability cannot be fully considered, and it highly depends on the experience of designers. This results in a complex design process, a long iteration cycle, a large amount of resource consumption, and the advantage of low cost of small UAVs cannot be exerted. Summary of the Invention
[0003] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a collaborative design method for the aerodynamics and handling and stability of a UAV, which can solve the problems in the above prior art.
[0004] The technical solution of the present invention: A collaborative design method for the aerodynamics and handling and stability of a UAV, wherein the method includes:
[0005] S100, establishing a parametric model to parameterize the structure to be optimized of the UAV;
[0006] S102, establishing an optimization model to perform mesh generation and mesh quality optimization on the external flow field of the UAV;
[0007] S104, establishing a calculation model to batch-calculate the aerodynamic force data of the UAV under multiple working conditions and post-process the aerodynamic force data into a data packet in a predetermined format;
[0008] S106, importing the data packet in the predetermined format and using the coefficient freezing method to extract the aerodynamic force data required for the characteristic flight stages of the UAV from the data in the data packet;
[0009] S108, judging whether the UAV meets the flight quality requirements according to the extracted aerodynamic force data and the pre-stored flight quality judgment table;
[0010] S110, when the flight quality requirements are not met, adjusting the UAV control system parameters;
[0011] S112, mapping the adjusted UAV control system parameters to the aerodynamic layout and performing iterative calculations until the UAV meets the maximum lift-to-drag ratio requirement and the flight quality requirements.
[0012] Preferably, the parameters of the UAV control system are adjusted by plotting a Bode plot or a Nyquist plot.
[0013] Preferably, the structure to be optimized includes one or more of the following: wingspan, aspect ratio, and relative position of the front and rear wings.
[0014] Preferably, the data packet in a predetermined format is a.bin data packet.
[0015] Preferably, the parameters of the UAV control system include the feedforward gain parameter, damping coefficient, and step integral coefficient of the pitch channel.
[0016] Preferably, Isight is used to execute S100 - S104, and Matlab is used to execute S106 - S112.
[0017] Through the above technical solutions, the overall design process of the UAV can be optimized, taking into account the requirements of multiple disciplinary fields such as aerodynamic performance, handling and stability, and structural strength. The optimal solution of the design goal is achieved through collaborative optimization design, solving the problems of complex design process, long iteration cycle, and large resource consumption in the prior art. Description of the Drawings
[0018] The accompanying drawings included are used to provide a further understanding of the embodiments of the present invention, which form a part of the specification, illustrate the embodiments of the present invention, and together with the written description, explain the principles of the present invention. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.
[0019] Figure 1 It is a flowchart of a collaborative design method for the aerodynamic and handling and stability of a UAV provided by an embodiment of the present invention;
[0020] Figure 2 It is a schematic diagram of the composition of the state - space matrix of the longitudinal short - period mode in an embodiment of the present invention;
[0021] Figure 3 It is a Bode plot of the longitudinal short - period mode in an embodiment of the present invention;
[0022] Figure 4 It is the optimized Bode plot of the longitudinal short - period mode in an embodiment of the present invention. Detailed Embodiments
[0023] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the following description, for purposes of explanation and not limitation, specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details.
[0024] It should be noted here that, in order to avoid obscuring the present invention with unnecessary details, only the device structures and / or processing steps closely related to the solution according to the present invention are shown in the drawings, while other details less relevant to the present invention are omitted.
[0025] Figure 1 It is a flowchart of a collaborative design method for the aerodynamics and handling and stability of an unmanned aerial vehicle provided by an embodiment of the present invention.
[0026] For example, the method described in the present invention can be applied to the collaborative design of the aerodynamics and handling and stability of low-speed small unmanned aerial vehicles.
[0027] Among them, low speed means a flight speed less than 100 m / s; a small unmanned aerial vehicle means a small unmanned aerial vehicle with a wingspan less than 3 m and a weight less than 30 kg.
[0028] As Figure 1 shown, a collaborative design method for the aerodynamics and handling and stability of an unmanned aerial vehicle, wherein the method includes:
[0029] S100, establishing a parametric model to parameterize the structure to be optimized of the unmanned aerial vehicle;
[0030] S102, establishing an optimization model to perform mesh generation and mesh quality optimization on the external flow field of the unmanned aerial vehicle;
[0031] S104, establishing a calculation model to batch-calculate the aerodynamic force data of the unmanned aerial vehicle under multiple working conditions and post-process the aerodynamic force data into data packets in a predetermined format;
[0032] S106, importing the data packets in the predetermined format and using the coefficient freezing method to extract the aerodynamic force data required for the characteristic flight phases of the unmanned aerial vehicle from the data in the data packets;
[0033] S108, judging whether the unmanned aerial vehicle meets the flight quality requirements according to the extracted aerodynamic force data and the pre-stored flight quality judgment table;
[0034] S110, when the flight quality requirements are not met, adjusting the control system parameters of the unmanned aerial vehicle;
[0035] S112, mapping the adjusted control system parameters of the unmanned aerial vehicle to the aerodynamic layout and performing repeated iterations until the unmanned aerial vehicle meets the maximum lift-drag ratio requirement and the flight quality requirement.
[0036] Through the above technical solution, the overall design process of the unmanned aerial vehicle (UAV) can be optimized. By comprehensively considering the requirements of multiple disciplinary fields such as aerodynamic performance, handling and stability, and structural strength, the optimal solution of the design goal can be achieved through collaborative optimization design, solving the problems of complex design process, long iteration cycle, and large resource consumption in the prior art.
[0037] According to an embodiment of the present invention, the parameters of the UAV control system are adjusted by plotting a Bode diagram or a Nyquist diagram.
[0038] According to an embodiment of the present invention, the structure to be optimized includes one or more of the following: wingspan, aspect ratio, and relative position of the front and rear wings.
[0039] According to an embodiment of the present invention, the data packet in a predetermined format is a.bin data packet.
[0040] According to an embodiment of the present invention, the parameters of the UAV control system include the feedforward gain parameter, damping coefficient, and step integral coefficient of the pitch channel.
[0041] According to an embodiment of the present invention, Isight is used to execute S100 - S104, and Matlab is used to execute S106 - S112.
[0042] The collaborative design method for the aerodynamic and handling and stability of the UAV according to the present invention will be described below with reference to examples.
[0043] In the discipline of control system design, the handling and stability of an aircraft can be evaluated by flight quality, which can be divided into two categories: longitudinal flight quality and lateral - directional flight quality. Among them, the longitudinal flight quality includes longitudinal short - period mode and longitudinal long - period mode; the lateral - directional flight quality includes roll - convergence mode, Dutch roll mode, and spiral - divergence mode; the evaluation index systems of each mode need to meet the conditions in Table 1 below.
[0044] Table 1 Flight Quality Index
[0045] Damping ratio ζ Frequency Ω Others Longitudinal short-period mode ＞0.35 ＞0.28 Longitudinal long-period mode ＞0.04 Roll convergence mode TR < 1 s Dutch roll mode ＞0.19 ＞0.4 Spiral divergence mode T2 > 12 s
[0046] Among them, TR is the time constant of the roll - convergence mode. The smaller this value is, the shorter the convergence time and the more stable it is; T2 is the attitude multiplication time constant of the spiral - divergence mode. The larger this value is, the longer the time required for attitude divergence, and the better (because this mode usually cannot converge, and it is necessary to control its divergence time constant > the driver's physiological reaction time).
[0047] In the aerodynamic design of unmanned aerial vehicles (UAVs), the design goal is usually to maximize the lift-to-drag ratio of the aircraft under specific flight conditions. Specifically, it is manifested as an aerodynamic layout with high lift and low drag for the aircraft. Among the drag forces, there is an induced drag that is coupled with the lift force. That is, the higher the lift, the induced drag increases in a quadratic relationship, namely the induced drag
[0048] where \(C_{d_{ind}}\) is the induced drag, which is generated along with the lift force. As long as there is lift, induced drag will surely be generated; \(k\) is the induced drag coefficient, which can be determined through experimental data; is the square of the lift force, and the induced drag is proportional to the square value of the lift force.
[0049] Therefore, in the optimization design of the aircraft, it is necessary to optimize the aerodynamic layout to reduce the induced drag coefficient \(k\) without degrading the flight performance of the aircraft. At this time, the aerodynamics and handling stability can be considered jointly. The collaborative design method is as follows:
[0050] First, establish the overall aerodynamic simulation process using Isight:
[0051] (1) Establish a Simcode module, embed bat batch commands to run Catia, and parameterize the aircraft model parameters that need to be optimized. The structural parameters that can be optimized, such as wingspan, aspect ratio, and relative position of the front and rear wings, can be selected for parameterization.
[0052] (2) Establish a Simcode module, embed bat batch commands to run the FluentMesh module, and through writing a.jou script file, make FluentMesh automatically perform mesh generation and mesh quality optimization for the external flow field of the aircraft.
[0053] (3) Establish a Simcode module, embed bat batch commands to run the FluentSolve module, and through writing a.jou script file, batch-calculate the aerodynamic force data of the aircraft under multiple working conditions, and at the same time post-process the aerodynamic data into a standard form of.bin data packet.
[0054] Secondly, write a flight performance analysis script using Matlab:
[0055] (1) Import the.bin data packet processed into the standard form into the Matlab script, and use the coefficient freezing method to extract the aerodynamic force data required for the characteristic flight stage (for example, the stage when the aircraft is flying at a certain flight altitude and a certain flight speed). Among them, the example state space matrix corresponding to the extracted aerodynamic force data is as Figure 2 shown, and this matrix can reflect the characteristic flight state of the aircraft.
[0056] (2) Judge whether the aircraft meets the requirements according to the flight quality judgment table. If the flight quality requirements are not met, adjust the parameters of the aircraft control system by drawing a Bode plot or a Nyquist plot.
[0057] (3) Map the parameters of the aircraft control system to the aerodynamic layout, and iterative operations can be carried out until the aircraft meets the requirements of the maximum lift-to-drag ratio (the ratio of lift to drag) and the flight quality requirements.
[0058] Features described and / or illustrated for one embodiment above can be used in the same or similar manner in one or more other embodiments, and / or combined with or replace features in other embodiments.
[0059] It should be emphasized that the term "comprising / including" as used herein refers to the presence of features, whole units, steps or components, but does not exclude the presence or addition of one or more other features, whole units, steps, components or combinations thereof.
[0060] The above devices and methods of the present invention can be implemented by hardware or by a combination of hardware and software. The present invention relates to such a computer-readable program that, when executed by a logic component, can enable the logic component to implement the above-described device or constituent components, or enable the logic component to implement the above-described various methods or steps. The present invention also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, etc.
[0061] Many features and advantages of these embodiments are apparent from this detailed description, and thus the appended claims are intended to cover all such features and advantages of these embodiments that fall within their true spirit and scope. In addition, since many modifications and changes are readily envisioned by those skilled in the art, the embodiments of the present invention are not to be limited to the exact structures and operations illustrated and described, but may cover all suitable modifications and equivalents falling within their scope.
[0062] The parts not described in detail in the present invention are well-known technologies to those skilled in the art.
Claims
1. A collaborative design method for aerodynamics and handling stability of an unmanned aerial vehicle, characterized in that: The method includes: S100, establishing a parameterized model to parameterize the structure of the UAV to be optimized; S102, establishing an optimization model to perform mesh division and mesh quality optimization on the external flow field of the UAV; S104, establishing a calculation model to batch calculate the aerodynamic data of the UAV under multiple working conditions, and post-processing the aerodynamic data into a data packet in a predetermined format; S106, importing a data packet in a predetermined format, and using a coefficient freezing method to extract aerodynamic data required for the characteristic flight phase of the UAV from the data in the data packet; S108, judging whether the UAV meets the flight quality requirements according to the extracted aerodynamic data and the pre-stored flight quality judgment table; S110, if the flight quality requirements are not met, the control system parameters of the UAV are adjusted; S112, mapping the adjusted UAV control system parameters to the aerodynamic layout, and performing repeated iterations until the UAV meets the maximum lift-to-drag ratio requirements and the flight quality requirements.
2. The method according to claim 1, characterized in that Adjust the parameters of the UAV control system by drawing Bode diagrams or Nyquist diagrams.
3. The method according to claim 2, characterized in that The structure to be optimized includes one or more of the following: wingspan, aspect ratio and relative position of front and rear wings.
4. The method according to claim 3, characterized in that The data packet of the predetermined format is a .bin data packet.
5. The method according to claim 4, characterized in that The parameters of the UAV control system include the feedforward gain parameter, damping coefficient and step integral coefficient of the pitch channel.
6. The method according to claim 1, characterized in that S100-S104 were performed using Isight, and S106-S112 were performed using Matlab.