Structural layout assessment method based on static stability analysis

Abstract

The present invention discloses a structural layout evaluation method based on static stability analysis, which relates to the field of balance test technology. The method includes: determining the aerodynamic main structure of the target flying car; constructing a three-dimensional environmental flow field, performing three-dimensional modeling and system aerodynamic mechanism twinning, and generating an aerodynamic model; determining multi-element aerodynamic scenarios, fitting multi-scenario evaluation results, and determining a first evaluation result; reading redundant layout and fault-tolerant control, collaboratively performing static stability tolerance analysis, and determining a second evaluation result; identifying non-static stability data and tracing the source, generating a single defect column; and comprehensively performing structural layout evaluation, and visualizing the terminal display interface. The method solves the technical problems that the aerodynamic main structure layout in the existing structural layout evaluation is unreasonable, and it is difficult to simulate the airflow changes under different flight conditions, which leads to poor comprehensiveness and accuracy of stability analysis, and makes the structural layout evaluation result inaccurate, and achieves the technical effect of improving flight stability, controllability and safety.

Description

Technical Field

[0001] The present application relates to the technical field related to balance testing, and in particular to a structural layout evaluation method based on static stability analysis. Background Art

[0002] With the rapid development of science and technology, flying cars, as an important carrier of future transportation, are increasingly attracting global attention for their design and research and development. Flying cars not only need to have the driving ability of traditional cars, but also need to fly stably in the air, which puts extremely high demands on the aerodynamic performance of the structural layout. The main aerodynamic structure of a flying car is the basis of its flight performance. Its design needs to comprehensively consider multiple factors such as the center of mass, center of lift, thrust line and balance plane. The reasonable layout of these elements is directly related to the stability and controllability of the flying car. Traditional stability analysis mainly focuses on the longitudinal, lateral and side stability of the flying car, that is, whether the flying car can quickly return to a stable state after being disturbed by the outside world. However, with the complexity of the design of flying cars, traditional stability analysis methods can no longer meet the needs.

[0003] Therefore, in the current structural layout assessment related technologies, there are technical problems such as unreasonable aerodynamic main structure layout and difficulty in simulating airflow changes under different flight conditions, which in turn leads to poor comprehensiveness and accuracy of stability analysis and inaccurate structural layout assessment results. Summary of the invention

[0004] The present application provides a structural layout assessment method based on static stability analysis, and adopts technical means such as three-dimensional environmental flow field, system aerodynamic mechanism twinning, multi-element aerodynamic scenario simulation, redundant layout and fault-tolerant control. It solves the technical problems existing in the existing structural layout assessment, such as unreasonable layout of the aerodynamic main structure, difficulty in simulating airflow changes under different flight conditions, which leads to poor comprehensiveness and accuracy of stability analysis and inaccurate structural layout assessment results, thereby achieving the technical effect of improving flight stability, controllability and safety.

[0005] The present application provides a structural layout evaluation method based on static stability analysis, the method comprising: determining the aerodynamic main structure of the target flying car, wherein the aerodynamic main structure is a structural layout determined at least based on the center of mass, the center of lift, the inference line and the balance plane; constructing a three-dimensional environmental flow field, combining the aerodynamic main structure to perform three-dimensional modeling and system aerodynamic mechanism twinning to generate an aerodynamic model, wherein the three-dimensional environmental flow field can perform multi-scenario simulation switching, the system aerodynamic mechanism is determined based on multi-system collaboration, and the aerodynamic model is a twin network structure; determining multi-element aerodynamic scenarios, combining the aerodynamic model to perform scenario simulation It is simulated to perform static stability analysis based on reverse restoring force, fit multi-scenario evaluation results, and determine a first evaluation result, wherein the static stability analysis includes traditional static stability dimension and relaxed static stability dimension; based on the aerodynamic main structure and the aerodynamic mechanism of the system, the redundant layout and fault-tolerant control are read, and static stability tolerance analysis is performed collaboratively to determine the second evaluation result; the first evaluation result and the second evaluation result are fitted, non-static stability data is identified and traced, and a defect list is generated, wherein the defect list includes structural layout defects; based on the defect list, a structural layout evaluation is performed in a coordinated manner, and the terminal display interface is visualized.

[0006] In a possible implementation, system aerodynamic mechanism twinning is performed, and the following processing is performed: reading the configuration system of the target flying car, performing a system autonomous evaluation based on static stability correlation, and determining a first system characteristic; performing a collaborative evaluation based on static stability correlation, and determining a second system characteristic; and performing system aerodynamic mechanism twinning with the first system characteristic and the second system characteristic as constraints.

[0007] In a possible implementation, the structural layout evaluation method based on static stability analysis performs the following processing: the traditional static stability dimension is static stability restoration, the relaxed static stability dimension is cross-state static stability restoration, and the relaxed static stability dimension is dynamic response stabilization based on the flight control system.

[0008] In a possible implementation, the structural layout evaluation method based on static stability analysis also performs the following processing: interactive static stability control recording, data mining and setting of disturbance threshold; if the scene flow field disturbance is less than the disturbance threshold, traditional static stability control is performed; if the scene flow field disturbance is greater than the disturbance threshold, relaxed static stability control is performed.

[0009] In a possible implementation, the determining of the first evaluation result further performs the following processing: the aerodynamic model includes a first branch and a second branch, the first branch is used for traditional static stability analysis, and the second branch is used for relaxed static stability analysis; determining a first simulation scenario, performing scenario restoration and static stability recovery simulation on the first branch and the second branch, and determining branch simulation data; determining an instability evaluation criterion, evaluating and fitting the branch simulation data, and determining a first scenario evaluation result.

[0010] In a possible implementation, the branch simulation data is evaluated and fitted, and the following processing is also performed: determining a static stability index set and the instability assessment standard; determining an axial direction based on the static stability index set and time, and establishing a time phase multivariate coordinate system; performing data conversion based on the branch simulation data in combination with the time phase multivariate coordinate system, and determining a time phase trend, wherein a time phase includes static stability-instability-restability; performing an assessment based on the time phase trend in combination with the instability assessment standard, and determining a first scenario assessment result, wherein the assessment dimensions include single structure instability and collaborative instability.

[0011] In a possible implementation, after generating a single defect column, the following processing is also performed: traversing the monitoring data set to perform mean calculation and obtain a first monitoring mean; based on the structural layout defects, performing a finite element-based multi-objective iterative optimization to determine the target optimization strategy; taboo locking the strategy adjustment method that meets the preset optimization degree, and using the preset number of iterations as the taboo unlocking method.

[0012] In a possible implementation, the multi-objective iterative optimization based on finite elements performs the following processing: randomly determine a first number of pre-adjustment defects, perform perturbation optimization, and determine a first strategy set, wherein the optimization degree of static stability index is used as the optimization judgment criterion, randomly determine a second number of pre-adjustment defects, perform perturbation optimization, and determine a second strategy set, wherein the first number and the second number are positive integers greater than or equal to 1 and less than or equal to the total number of defects, and the first number and the second number have no correlation; perform iterative optimization until the convergence condition is met, calibrate the first strategy set, the second strategy set, and up to the Nth strategy set, and select the target optimization strategy.

[0013] It is intended to determine the aerodynamic main structure of the target flying car through the structural layout evaluation method based on static stability analysis proposed in this application, wherein the aerodynamic main structure is a structural layout determined at least based on the center of mass, center of lift, inference line and balance plane; construct a three-dimensional environmental flow field, combine the aerodynamic main structure to perform three-dimensional modeling and system aerodynamic mechanism twinning, and generate an aerodynamic model, wherein the three-dimensional environmental flow field can perform multi-scenario simulation switching, the system aerodynamic mechanism is determined based on multi-system collaboration, and the aerodynamic model is a twin network structure; determine multi-element aerodynamic scenarios, combine the aerodynamic model to perform scenario simulation and Based on the static stability analysis of the reverse restoring force, the multi-scenario evaluation results are fitted to determine the first evaluation result, wherein the static stability analysis includes the traditional static stability dimension and the relaxed static stability dimension; based on the aerodynamic main structure and the aerodynamic mechanism of the system, the redundant layout and fault-tolerant control are read, and the static stability tolerance analysis is carried out in coordination to determine the second evaluation result; the first evaluation result and the second evaluation result are fitted, the non-static stability data is identified and traced, and a defect list is generated, wherein the defect list includes structural layout defects; based on the defect list, the structural layout evaluation is carried out in a coordinated manner, and the terminal display interface is visualized. The technical problems existing in the existing structural layout evaluation, such as the unreasonable layout of the aerodynamic main structure and the difficulty in simulating the changes in airflow under different flight conditions, which in turn lead to the poor comprehensiveness and accuracy of the stability analysis and the inaccurate results of the structural layout evaluation, are solved, and the technical effect of improving flight stability, controllability and safety is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of a flow chart of a structural layout evaluation method based on static stability analysis provided in an embodiment of the present application;

[0016] Figure 2 A schematic diagram of the process of performing system aerodynamic mechanism twinning in the structural layout evaluation method based on static stability analysis provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0020] The present application embodiment provides a structural layout evaluation method based on static stability analysis, such as Figure 1 As shown, the method includes:

[0021] Step S100, determine the main aerodynamic structure of the target flying car, wherein the main aerodynamic structure is a structural layout determined at least based on the center of mass, center of lift, thrust line and balance plane. Determining the main aerodynamic structure of the target flying car means constructing and optimizing the main structural layout of its aerodynamic characteristics based on a series of key elements when designing a flying car. The key elements include at least the center of mass, center of lift, thrust line and balance plane, which together determine the stability and maneuverability of the flying car in the air. Specifically, the center of mass is the center point of all the mass of the flying car. During the design process, it is necessary to accurately calculate and reasonably arrange the center of mass position to ensure that the flying car can maintain balance in various flight conditions. The lift center is the main area that generates lift, usually located on the wing or other lift components. When designing a flying car, it is necessary Optimize the position and shape of the lift center to improve lift efficiency and reduce drag; the thrust line refers to the line of action of the thrust generated by the engine. The direction and size of the thrust line directly affect the flight performance and stability. In the design process of flying cars, it is necessary to accurately calculate the thrust line and reasonably arrange the engine position to ensure that the thrust can be effectively converted into flight power; the balance surface refers to the wing surface or control surface used to maintain the balance of the flying car. These surfaces can adjust the flight attitude and change the lift and drag distribution, thereby achieving precise control of the flying car. In the design process, the balance surface needs to be reasonably arranged and its interaction with other aerodynamic components needs to be considered. The main aerodynamic structure layout determined based on these factors usually includes the structural dimensions, layout and other characteristics of the flying car fuselage, tail and wings. For example, different types of wing layouts such as fixed wings, rotors, tilt-rotor wings or ducted fans should select the appropriate layout form according to flight requirements and performance requirements; consider factors such as the center of mass position, streamlined design and internal space layout to ensure that the fuselage can meet flight requirements and has good aerodynamic characteristics; arrange the engine position and direction reasonably, and design an efficient thrust system to provide sufficient thrust and good maneuverability; configure appropriate control surfaces (such as elevators, rudders, etc.) according to flight control requirements, and optimize their position and shape to achieve precise flight control.

[0022] Step S200, construct a three-dimensional environmental flow field, combine the aerodynamic main structure to perform three-dimensional modeling and system aerodynamic mechanism twinning, and generate an aerodynamic model, wherein the three-dimensional environmental flow field can perform multi-scene simulation switching, the system aerodynamic mechanism is determined based on multi-system collaboration, and the aerodynamic model is a twin network structure. The three-dimensional environmental flow field refers to the use of computer simulation technology to construct the airflow environment in the three-dimensional space where the flying car is located under different flight conditions. This three-dimensional environmental flow field can simulate the changes in meteorological conditions such as wind speed, wind direction, and air pressure, as well as the influence of environmental factors such as terrain and buildings on airflow. By constructing a three-dimensional environmental flow field, it can provide real and reliable data support for the subsequent establishment of aerodynamic models. After determining the main aerodynamic structure of the flying car, the three-dimensional modeling software is used to accurately model it, including the precise representation of the geometric shape, size and relative position of each component such as wings, fuselage, engine, control surface, etc. Through three-dimensional modeling, the aerodynamic shape of the flying car can be intuitively displayed. The system aerodynamic mechanism twin refers to the combination of the aerodynamic system of the flying car with the digital twin technology. By constructing the digital twin of the pneumatic system, the real-time monitoring, simulation and optimization of the actual aerodynamic system can be realized. In this process, multiple systems such as the three-dimensional environmental flow field, the three-dimensional aerodynamic model and the control system of the flying car need to be coordinated to ensure that the digital twin can accurately reflect the operating status of the actual aerodynamic system. On the basis of the construction of three-dimensional environmental flow field, three-dimensional modeling and system aerodynamic mechanism twin, the aerodynamic model of the flying car can be generated. This model is a comprehensive model that includes the geometric shape, aerodynamic performance parameters, control system and other aspects of the flying car. Through the aerodynamic model, the flight performance of the flying car can be simulated and predicted. Specifically, the three-dimensional environmental flow field supports multi-scene simulation switching function, which means that the aerodynamic performance of the flying car under different flight conditions can be simulated. These scenes include different meteorological conditions such as wind speed, wind direction, and air pressure, as well as different terrains, buildings and other environmental factors. By switching different scenes, the flight performance and stability of the flying car under various conditions can be comprehensively evaluated; the aerodynamic model, as part of the twin network structure, is closely integrated with the digital twin technology. The twin network structure collects and transmits the data of the actual aerodynamic system to the digital twin in real time, so as to realize real-time monitoring and prediction of aerodynamic performance. At the same time, the digital twin can also feed back the simulation results to the actual system to guide design optimization and flight control decisions, thereby greatly improving the design efficiency and flight safety of the flying car.

[0023] In one possible implementation, Figure 2As shown, step S200 further includes step S210, reading the configuration system of the target flying car, performing a system autonomous evaluation based on static stability correlation, and determining a first system characteristic. Reading the configuration system of the target flying car specifically refers to obtaining the detailed configuration information of the flying car from the database of the flying car, including but not limited to the power system, control system, structural layout, aerodynamic design, etc.; performing system autonomous evaluation based on static stability correlation, that is, using the built-in system of the flying car, based on the configuration information and static stability correlation of the flying car, independently evaluating each subsystem of the flying car, and determining the performance of the flying car in terms of static stability, including but not limited to the stability of the flight attitude, the control ability of the flight speed, etc. Specifically, in the flying car, static stability (static stability) refers to the ability of the flying car to resist external disturbances (such as wind, airflow changes, etc.) and maintain its flight state without external control input, and static stability correlation refers to the interaction and influence between various factors related to static stability. System performance and mutual influence will also affect the static stability state to a certain extent. For example, for the relaxation of the static stability dimension, it depends on the flight control system, and the system response, model processing, computing power, etc. will affect the actual control. Finally, through the system autonomous evaluation, the first system characteristics of the flying car in terms of static stability are determined, which may include the stability index of the flight attitude, the control range of the flight speed, the ability to maintain the flight altitude, etc.

[0024] The method further includes step S220, performing collaborative evaluation based on static stability correlation to determine the second system characteristics. Performing collaborative evaluation based on static stability correlation specifically refers to evaluating the overall performance of the flying car based on the interaction and influence between the various subsystems of the flying car. Through collaborative evaluation, the second system characteristics of the flying car in terms of static stability can be determined. These characteristics may focus more on the overall performance of the flying car, such as stability under different flight conditions, coordination and cooperation between the various subsystems, etc.

[0025] Step S200 also includes step S230, in which the aerodynamic mechanism twinning of the system is performed with the first system characteristic and the second system characteristic as constraints. A virtual flying car model is created using digital twin technology, and the model can simulate and predict the aerodynamic performance of the flying car under various aerodynamic conditions. The first system characteristic and the second system characteristic are used as important constraints to ensure that the virtual model can accurately reflect the performance characteristics of the actual flying car in terms of static stability during the simulation process. By inputting the first system characteristic and the second system characteristic as constraints, it can be ensured that the virtual model is consistent with the actual flying car in terms of static stability. Specifically, other data related to the aerodynamic performance of the flying car is collected, such as the geometry of the aerodynamic components, material properties, parameters of the flight environment, etc., and a virtual model of the flying car is constructed using modeling software. During the construction process, Special attention should be paid to incorporating the first system characteristics and the second system characteristics into the model as constraints to ensure that the model can accurately reflect these characteristics during the simulation process. Then, the aerodynamic performance is simulated using simulation software. By inputting different flight conditions and aerodynamic parameters, the response and performance of the virtual model under different conditions are observed. The simulation results are compared and verified with experimental data or actual flight data to evaluate the accuracy and reliability of the virtual model. According to the simulation results and verification feedback, the virtual model is optimized, such as adjusting the layout, shape or material properties of the aerodynamic components to improve the static stability and aerodynamic performance of the flying car. Through continuous iteration and optimization, the flying car model is obtained, that is, the system aerodynamic mechanism twin is completed.

[0026] Step S300, determining a multivariate aerodynamic scenario, combining the aerodynamic model to perform scenario simulation and static stability analysis based on reverse restoring force, fitting multi-scenario evaluation results, and determining a first evaluation result, wherein the static stability analysis includes a traditional static stability dimension and a relaxed static stability dimension. Multivariate aerodynamic scenarios refer to the construction of multiple different aerodynamic simulation scenarios based on various flight conditions and environmental factors that flying cars may encounter, which may include different meteorological conditions such as wind speed, wind direction, air pressure, temperature, and different environmental factors such as terrain, buildings, and obstacles. By constructing multivariate aerodynamic scenarios, the aerodynamic performance and stability of flying cars under different conditions can be comprehensively evaluated; after determining the multivariate aerodynamic scenarios, it is necessary to use the constructed aerodynamic model to simulate the scenarios. Through the aerodynamic model, the flight state and performance of flying cars in different scenarios are simulated, including speed, altitude, attitude, stability, etc.; static stability analysis is one of the important means to evaluate the stability of flying cars. In static stability analysis, reverse restoring force is a key concept, which refers to the ability of a flying car to automatically return to its original stable state when it is subjected to external disturbances (such as airflow changes, gusts, etc.). Based on the static stability analysis of reverse restoring force, the stability performance of flying cars in different scenarios can be evaluated, including its ability to resist disturbances, the speed and efficiency of restoring stability, etc. The traditional static stability dimension refers to the design of the flying car to maintain a certain static stability margin, that is, the aerodynamic center is located a certain distance behind the center of gravity, so that the aircraft can automatically generate a restoring torque when disturbed, thereby maintaining stability. This design method is more common in traditional fixed-wing aircraft. Its advantages are stable flight and easy control, but it may sacrifice certain maneuverability and performance; Relaxed static stability dimension refers to relaxing the requirements for the static stability margin of flying cars through active control technology and other means, and even allowing it to be in a statically unstable state within a certain range. This design method is more common in modern high-performance fighter jets. Its advantage is that it can greatly improve the maneuverability and performance of the aircraft, but it needs to rely on advanced flight control systems. The system and algorithm are used to ensure flight safety. In the design of relaxed static stability, the stability in flight is mainly achieved by active control systems (such as fly-by-wire flight control systems), and the stability and maneuverability of the aircraft are maintained by adjusting the deflection angle and speed of the control surface in real time. After completing the simulation and static stability analysis of multiple aerodynamic scenarios, the evaluation results of each scenario are fitted and comprehensively analyzed, including the comparison and trade-off of the evaluation results of traditional static stability dimensions and relaxed static stability dimensions, as well as the performance and stability requirements under different scenarios. By fitting the evaluation results of multiple scenarios, a comprehensive first evaluation result can be determined, which can comprehensively evaluate the aerodynamic performance and stability performance of the flying car under different conditions.

[0027] In a possible implementation, step S300 further includes: the traditional static stability dimension is static stability restoration, the relaxed static stability dimension is cross-state static stability restoration, and the relaxed static stability dimension is dynamic response stabilization based on the flight control system. The design of flying cars tends to maintain static stability, that is, the flying car can naturally return to its original flight state after being slightly disturbed. Traditional static stability is mainly determined by the aerodynamic layout of the flying car, especially the relative position of the aerodynamic center and the center of gravity. Static stability recovery means that when the flying car is disturbed by external factors (such as gusts, airflow changes, etc.), the traditional static stability design can generate sufficient restoring torque to enable the flying car to quickly and stably return to its original flight attitude and speed. The recovery process mainly depends on the aerodynamic characteristics and structural layout of the flying car, and no or little intervention from the flight control system is required; relaxed static stability design means that by adjusting the aerodynamic layout and control system of the flying car, the flying car can maintain or restore stability in a wider flight state, allowing the flying car to temporarily lose static stability under certain conditions, but maintain overall stability through the rapid response of the active control system. Cross-state static stability recovery means that the relaxed static stability design allows the flying car to maintain or restore stability in different flight states (such as subsonic In order to achieve static stability recovery at high speeds, supersonic speeds, climbing, descending, etc., the flight control system is required to have a high degree of dynamic response capability and adaptability, and be able to quickly adjust the control strategy to maintain the stability of the flying car according to different flight conditions and disturbance types; dynamic response stability control based on the flight control system refers to relaxing the core part of the static stability design, relying on advanced flight control systems to achieve dynamic stability control of the flying car. Specifically, the flight control system senses the state parameters of the flying car (such as attitude, speed, acceleration, etc.) and external disturbance information in real time, and uses complex control algorithms and strategies to quickly adjust the control surfaces of the flying car (such as rudders, thrust vectors, etc.) to generate the required control torque and thrust, thereby maintaining the stable flight of the flying car, which helps to improve the performance of the flying car and reduce the structural weight and cost. For example, by reducing the area and weight of the tail wing, the lift-to-drag ratio and fuel efficiency of the flying car can be improved; by optimizing the control strategy, the pilot's workload can be reduced and flight safety can be improved.

[0028] In a possible implementation, step S300 further includes step S310, interactive static stability control recording, data mining and setting disturbance threshold. Interactive static stability control recording refers to the process of real-time monitoring and recording of the static stability and control input of the flying car during flight, including real-time data of parameters such as the attitude, speed, acceleration, and control surface deflection of the flying car. Through these records, the control characteristics and stability performance of the flying car can be analyzed, useful information and patterns can be extracted from them, and the stability and control characteristics of the flying car under different flight conditions and disturbance types can be identified, and then the disturbance threshold is set. It also includes step S320, if the scene flow field disturbance is less than the disturbance threshold, perform traditional static stability control. When the scene flow field disturbance is less than the set disturbance threshold, the traditional static stability control strategy is executed, that is, the flying car relies on its inherent aerodynamic characteristics and structural layout to maintain stability, without or rarely requiring active intervention of the flight control system. It also includes step S330, if the scene flow field disturbance is greater than the disturbance threshold, perform relaxed static stability control. When the scene flow field disturbance is greater than the set disturbance threshold, the relaxed static stability control strategy is executed, that is, the flying car will temporarily give up some static stability and maintain overall stability through the rapid response and dynamic adjustment of the flight control system, significantly improving the maneuverability and response speed of the flying car, enabling it to better adapt to the complex and changeable flight environment.

[0029] In a possible implementation, step S300 further includes step S340, wherein the aerodynamic model includes a first branch and a second branch, wherein the first branch is used for performing a traditional static stability analysis, and the second branch is used for performing a relaxed static stability analysis. The first branch is a traditional static stability analysis branch, which focuses on simulating and evaluating the performance of the flying car under a traditional static stability state, and mainly relies on the aerodynamic layout and inherent stability characteristics of the flying car, such as the relative position of the aerodynamic center and the center of gravity, etc., to simulate the natural recovery process of the flying car when it is subjected to slight disturbances (such as gusts, airflow changes, etc.) to evaluate its static stability; the second branch is a relaxed static stability analysis branch, which focuses on simulating and evaluating the performance of the flying car under a relaxed static stability state. The relaxed static stability design allows the flying car to maintain or restore stability under a wider range of flight conditions, but relies on the rapid response and dynamic adjustment of the flight control system, and simulates the dynamic response process of the flying car under large disturbances or complex flight environments to evaluate the effectiveness and stability of its control system.

[0030] The method further includes step S350, determining a first simulation scene, performing scene restoration and static stability recovery simulation on the first branch and the second branch, and determining branch simulation data. According to the parameters such as the initial state, flight conditions, disturbance type and size of the flying car, a specific simulation scene is determined, and scene restoration and static stability recovery simulation are performed in the first branch and the second branch respectively, that is, in the first branch, the natural recovery process of the flying car after being disturbed is simulated, and in the second branch, the dynamic stability process of the flying car under the control system is simulated, and the simulation data of the first branch and the second branch are determined respectively.

[0031] The method further includes step S360, determining an instability evaluation standard, evaluating the branch simulation data and fitting the data, and determining the first scenario evaluation result. The instability evaluation standard may include indicators such as the attitude change range, speed fluctuation, and acceleration response of the flying car, which are used to measure the stability performance of the flying car in the simulation scenario. According to the instability evaluation standard, the simulation data of the first branch and the second branch are evaluated in detail, and the stability performance difference of the two branches under the same disturbance is compared. The evaluation results are processed by data fitting to determine the first scenario evaluation result, including the evaluation of the effectiveness, applicability, and potential improvement direction of the traditional static stability analysis and the relaxed static stability analysis.

[0032] In a possible implementation, step S360 further includes step S361, determining a static stability index set and the instability assessment standard. Based on the design features of the flying car, the flight mission requirements, and the specific goals of the stability analysis, a static stability index set is determined. The static stability index set is a set of parameters used to quantitatively assess the static stability of the flying car, usually including but not limited to the attitude angle (such as pitch angle, roll angle, yaw angle), angular velocity, acceleration, control surface deflection angle, aerodynamic center position, center of gravity position, etc. of the flying car; considering the performance limitations, safety requirements, and uncertainties of the actual flight environment of the flying car, an instability assessment standard is formulated. The instability assessment standard is a series of criteria used to determine whether the flying car is in an unstable state, which may be based on the attitude change range, speed fluctuation, acceleration response, control system response time, and other aspects of the flying car.

[0033] The method further includes step S362, determining the axis based on the static stability index set and time, and establishing a time-phase multivariate coordinate system. After the static stability index set is determined, these indicators are used as the axis (or dimension) of the coordinate system, and time is introduced as another key axis to construct a multidimensional time-phase space for describing the static stability state of the flying car at different time points, that is, to establish a time-phase multivariate coordinate system, in which each point represents the static stability state of the flying car at a specific time point.

[0034] The method further includes step S363, wherein data conversion is performed based on the branch simulation data and in combination with the time phase multivariate coordinate system to determine the time phase trend, wherein the time phase includes static steady state-instability-restoration. Based on the branch simulation data (i.e., the simulation results of the traditional static stability analysis and the relaxed static stability analysis), data conversion is performed in combination with the time phase multivariate coordinate system, and the key parameters in the simulation data are mapped to the corresponding axis of the time phase coordinate system. In the time phase multivariate coordinate system, by observing and analyzing the changing trend of the static stability state of the flying car over time, different time phases such as static steady state, instability and restoration can be identified, i.e., the time phase includes static steady state-instability-restoration. Specifically, relatively stable or slowly changing sections are found in the time series data, and these sections correspond to the static steady state stage of the flying car; points or sections that deviate sharply from the original trajectory are found in the time series data, and these points or sections correspond to the instability stage of the flying car; and whether there is a trend of gradually returning to the static steady state after instability is observed in the time series data, and these trends correspond to the restoration stage of the flying car.

[0035] The method further includes step S364, in which an assessment is performed based on the time phase trend in combination with the instability assessment standard to determine a first scenario assessment result, wherein the assessment dimensions include single structure instability and coordinated instability. Based on the phase trend and instability assessment criteria, the assessment first needs to clarify the specific conditions and requirements of the first scenario, and combine the assessment results of single structure instability and coordinated instability to conduct a comprehensive analysis of the stability of the flying car and determine the assessment results of the first scenario. Specifically, single structure instability refers to the phenomenon that a single structure or component in a flying car loses stability under specific conditions, usually due to factors such as the mechanical properties, geometric shape, boundary conditions, etc. of the structure or component. Single structure instability assessment is usually used to analyze the stability of key components in flying cars (such as wings, tail wing, landing gear, etc.). By evaluating these components separately, potential stability problems can be discovered and solved in a timely manner; coordinated instability refers to the instability phenomenon caused by the interaction between multiple structures or components in a flying car, including the dynamic coupling and mutual influence between multiple structures or components. Coordinated instability assessment is usually used to analyze the stability of the entire flying car. By comprehensively analyzing the interaction between multiple structures or components, the overall stability performance of the flying car under different working conditions and external excitations is evaluated.

[0036] Step S400, based on the aerodynamic main structure and the aerodynamic mechanism of the system, redundant layout and fault-tolerant control are read, static stability tolerance analysis is performed in coordination, and a second evaluation result is determined. In the design and development of the flying car, the static stability tolerance of the flying car is comprehensively evaluated by comprehensively considering the layout of the aerodynamic main structure, the synergy of the aerodynamic mechanism of the system, the design of the redundant layout, and the implementation of the fault-tolerant control strategy. Specifically, the aerodynamic main structure is the core part of the design of the flying car, including the layout and shape design of key components such as wings, fuselage, and tail wing. The aerodynamic mechanism of the system refers to the collaborative working mode between various aerodynamic systems (such as propulsion system, control system, etc.) in the flying car, and through interaction, the flight mission of the flying car is jointly realized. Redundant layout refers to adding additional systems or components in the design of the flying car to improve the reliability and fault tolerance of the system. For example, adding redundant sensors and actuators in the flight control system can still maintain stable control of the flying car when some components fail. Static stability tolerance refers to the ability of a flying car to maintain a stable flight state and have a certain degree of fault tolerance when subjected to external disturbances or internal faults. When conducting static stability tolerance analysis, it is necessary to comprehensively consider the layout of the main aerodynamic structure, the synergy of the system's aerodynamic mechanism, the design of redundant layouts, and the implementation of fault-tolerant control strategies. By simulating the flight state under different fault scenarios, the static stability tolerance of the flying car is evaluated, and corresponding improvement measures are determined. The flight state of the flying car under different fault scenarios is simulated using simulation equipment. These scenarios may include sensor failure, actuator failure, and pneumatic component damage. The simulation results are analyzed to evaluate the static stability tolerance of the flying car under different fault scenarios, such as whether the flying car can maintain stable flight and whether it has sufficient fault tolerance. Based on the data analysis results, the second evaluation result of the flying car is determined.

[0037] Step S500, fitting the first evaluation result and the second evaluation result, identifying non-static data and tracing the source, and generating a defect list, wherein the defect list includes structural layout defects. The first evaluation result and the second evaluation result are fitted to comprehensively evaluate the comprehensive performance of the flying car under different conditions, including its stability under normal conditions and its fault tolerance under fault conditions, identifying non-static data and tracing the source. Specifically, non-static data refers to data points or areas that do not meet the static stability requirements found during the evaluation process. Non-static data indicates that the flying car has stability problems or potential failure risks under specific conditions. For the identified non-static data, tracing analysis is required to determine the cause of its generation, such as the layout problem of the aerodynamic main structure, the coordination problem of the system aerodynamic mechanism, the lack of redundant layout, or the failure of the fault-tolerant control strategy; and then generating a defect list, wherein the defect list is a tool for recording and analyzing design defects, and includes all defect information found during the evaluation process. For flying cars, the defect list may include multiple types of defects (such as structural Structural layout defects refer to the situation in which the flying car has stability problems or performance degradation under certain conditions due to unreasonable or defective structural layout during the design process. The defects may include but are not limited to improper layout of aerodynamic components (such as unreasonable layout position, angle or shape design of key components such as wings and tail wings, which affects the lift, drag and stability of the flying car), unreasonable center of gravity position (if the center of gravity position is improperly designed, it may cause the flying car to pitch, roll or yaw during flight, etc.), insufficient structural strength (some parts of the structural layout may have insufficient strength and cannot withstand the loads and stresses during flight, resulting in structural damage or failure) and insufficient redundant layout (there are deficiencies in the redundant layout design of key systems or components, resulting in the inability to effectively replace or compensate for the functions of failed components when a failure occurs).

[0038] In a possible implementation, step S500 further includes step S510, based on the structural layout defects, performing multi-objective iterative optimization based on finite elements to determine the target optimization strategy. A comprehensive defect analysis of the structural layout of the flying car usually includes identifying stress concentration points, uneven material distribution, design redundancy or insufficiency, etc. in the structure. By analyzing these defects, the optimization goals and directions can be clarified. Finite element analysis is used to evaluate the structural performance under different design schemes, such as stress distribution, displacement, vibration characteristics, etc. Since the optimization of the structural layout of the flying car usually involves multiple conflicting goals (such as reducing weight, increasing strength, improving dynamic performance, etc.), a multi-objective optimization method is required. Multi-objective optimization aims to find a set of solutions to achieve the best balance between multiple goals. After multiple rounds of iterative optimization, a set of optimal solutions is obtained, which represents the design scheme that achieves the best balance between different goals, and the target optimization strategy is determined.

[0039] The method also includes step S520, wherein the strategy adjustment method that meets the preset optimization degree is taboo-locked, and the preset number of iterations is used as a taboo unlocking method. The taboo search algorithm is used to solve combinatorial optimization problems. The taboo table is introduced to avoid repeated searches of the solution space area that has been visited, thereby increasing the diversity and globality of the search. The taboo table records the solutions or solution features visited in the most recent iterations, and prohibits revisiting these solutions or solutions with the same features in subsequent iterations; taboo locking refers to temporarily locking the strategy adjustment method (i.e., a set of design parameters or design solutions) that meets the preset optimization degree in the taboo table to prevent repeated attempts in subsequent iterations and avoid falling into the local optimal solution. The preset number of iterations as a taboo unlocking method means that after reaching a certain number of iterations, the strategy adjustment method that was originally taboo-locked will be unlocked. While maintaining the search diversity, it also allows the algorithm to reconsider the previously excluded solutions or design solutions when necessary. By setting a reasonable number of iterations, the possibility of finding the global optimal solution can be increased while ensuring the search efficiency.

[0040] In a possible implementation, step S510 further includes step S511, randomly determining a first number of pre-adjustment defects, performing perturbation optimization, and determining a first strategy set, wherein the optimization degree of the static stability index is used as the optimization judgment criterion. First, a number (referred to as the first number) of pre-adjustment defects is randomly selected, and this number should be a positive integer greater than or equal to 1 and less than or equal to the total number of defects. Pre-adjustment defects refer to defect points or areas that are pre-set and prepared for adjustment during the optimization process. After determining the first number of pre-adjustment defects, these defects are perturbation optimized, that is, the position, size, shape and other parameters of the defects are adjusted to observe the impact of these changes on system performance (such as static stability index), and a series of different optimization schemes are obtained. These schemes constitute the first strategy set, and each strategy represents the optimization result under a specific pre-adjustment defect configuration.

[0041] It also includes step S512, randomly determining a second number of pre-adjustment defects, performing perturbation optimization, and determining a second strategy set, wherein the first number and the second number are positive integers greater than or equal to 1 and less than or equal to the total number of defects, and the first number and the second number are not correlated. Similar to the first number, but the randomly selected number is recorded as the second number, which should also be a positive integer greater than or equal to 1 and less than or equal to the total number of defects, and there is no correlation between the first number and the second number, that is, they are two independent random selection processes, and the second number of pre-adjustment defects is perturbation optimized, and a series of optimization schemes are also obtained to constitute the second strategy set, which is repeated multiple times, and a different number of pre-adjustment defects are randomly selected each time and perturbation optimization is performed, thereby obtaining multiple strategy sets (such as the third strategy set, the fourth strategy set... until the Nth strategy set), each strategy set contains an optimization scheme under a specific pre-adjustment defect configuration.

[0042] It also includes step S513, performing iterative optimization until the convergence condition is met, proofreading the first strategy set, the second strategy set, and the Nth strategy set, and selecting the target optimization strategy. After obtaining multiple strategy sets, iterative optimization begins, and the solutions in each strategy set are compared, evaluated, and adjusted to find the solution that performs best in terms of the static stability index or other performance indicators, and continues until the preset convergence condition is met (such as the improvement of the performance indicator is less than a certain threshold, the preset number of iterations is reached, etc.). During the iterative optimization process, each strategy set is proofread to ensure that the solutions in each strategy set are valid and meet the optimization objectives and constraints. After completing the iterative optimization and proofreading the strategy set, the target optimization strategy is selected from the multiple strategy sets according to the optimization objectives and performance indicator evaluation results. This strategy should be the best among all candidate strategies, that is, it can make the system performance reach the optimal or near-optimal state under the premise of meeting all constraints.

[0043] Step S600, based on the defect list, comprehensively conduct structural layout assessment and visualize the terminal display interface. According to the structural layout defects recorded in the defect list, conduct a structural layout assessment, comprehensively review the structural design of the flying car, and ensure that it can maintain stability and safety under various flight conditions. Specifically, conduct a detailed analysis of the structural layout defects in the defect list to understand the specific manifestations of the defects, the causes of the defects, and the possible consequences. Based on the defect analysis results, optimize the structural layout of the flying car, such as adjusting the layout position, angle or shape of the aerodynamic components, optimizing the center of gravity position, increasing the structural strength, improving the redundant layout, etc. The main purpose of visualizing the terminal display interface is to present the results of the structural layout assessment in an intuitive and easy-to-understand manner. Through visual display, It is possible to have a clearer understanding of the structural layout of the flying car, the existing defects and the effects of the improvement measures. The visualization content includes structural layout diagrams, defect annotations, performance data, etc. For example, the structural layout diagram shows the overall structural layout of the flying car, including the position, shape and size of each component; the existing structural layout defects and the specific location and method of the improvement measures are marked on the structural layout diagram; the performance data shows the performance data comparison of the flying car before and after optimization, such as lift coefficient, drag coefficient, and stability index. Among them, the terminal display interface may include multiple different terminal devices (such as computers, tablets, mobile phones, etc.), and they can all display and interact with information well.

[0044] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A structural layout assessment method based on static stability analysis, characterized in that: The method comprises: Determine the aerodynamic main structure of the target flying car, wherein the aerodynamic main structure is a structural layout determined based on at least the center of mass, the center of lift, the inference line and the balance plane; Construct a three-dimensional environmental flow field, combine the aerodynamic main structure to perform three-dimensional modeling and system aerodynamic mechanism twinning, and generate an aerodynamic model, wherein the three-dimensional environmental flow field can perform multi-scene simulation switching, the system aerodynamic mechanism is determined based on multi-system collaboration, and the aerodynamic model is a twin network structure; Determine a multivariate aerodynamic scenario, perform scenario simulation and static stability analysis based on reverse restoring force in combination with the aerodynamic model, fit the multi-scenario evaluation results, and determine a first evaluation result, wherein the static stability analysis includes a traditional static stability dimension and a relaxed static stability dimension; Based on the aerodynamic main structure and the aerodynamic mechanism of the system, redundant layout and fault-tolerant control are read, static stability tolerance analysis is collaboratively performed, and a second evaluation result is determined; Fitting the first evaluation result and the second evaluation result, identifying non-static data and tracing the source, and generating a defect single column, wherein the defect single column includes structural layout defects; Based on the defect list, a structural layout assessment is comprehensively performed, and a terminal display interface is visualized, wherein, based on the defect list, the structural layout assessment is comprehensively performed according to the structural layout defects recorded in the defect list, and the structural design of the target flying car is comprehensively assessed; Perform system pneumatic twinning including: Reading the configuration system of the target flying car, performing a system autonomy assessment based on static stability correlation, and determining a first system characteristic; Based on the static stability correlation, a collaborative evaluation is performed to determine the characteristics of the second system; Taking the first system characteristic and the second system characteristic as constraints, system pneumatic mechanism twinning is performed.

2. The structural layout evaluation method based on static stability analysis according to claim 1, characterized in that: The traditional static stability dimension is static stability restoration, the relaxed static stability dimension is cross-state static stability restoration, and the relaxed static stability dimension is dynamic response stabilization based on the flight control system.

3. The structural layout evaluation method based on static stability analysis according to claim 1, characterized in that: The method further comprises: Interactive static control recording, data mining and setting disturbance thresholds; If the scene flow field disturbance is less than the disturbance threshold, traditional static stability control is performed; If the scene flow field disturbance is greater than the disturbance threshold, relaxed static stability control is performed.

4. The structural layout evaluation method based on static stability analysis according to claim 1, characterized in that: The determining of the first evaluation result comprises: The aerodynamic model comprises a first branch and a second branch, wherein the first branch is used for performing a traditional static stability analysis, and the second branch is used for performing a relaxed static stability analysis; Determine a first simulation scene, perform scene restoration and static stability recovery simulation on the first branch and the second branch, and determine branch simulation data; Determine an instability assessment criterion, evaluate and fit the branch simulation data, and determine a first scenario assessment result.

5. The structural layout evaluation method based on static stability analysis according to claim 4, characterized in that: The step of evaluating the branch simulation data and performing fitting comprises: Determining a static stability index set and the instability assessment criteria; Based on the static stability index set and time, the axial direction is determined and a time-phase multivariate coordinate system is established; Based on the branch simulation data, data conversion is performed in combination with the time phase multivariate coordinate system to determine the time phase trend, wherein the time phase includes static steady state-instability-restability; Based on the time phase trend and in combination with the instability assessment standard, an assessment result of the first scenario is determined, and the assessment dimensions include single structure instability and coordinated instability.

6. The structural layout evaluation method based on static stability analysis according to claim 1, characterized in that: After the defect list is generated, it includes: Based on the structural layout defects, a multi-objective iterative optimization based on finite elements is performed to determine a target optimization strategy; Taboo locking is performed on the strategy adjustment method that meets the preset optimization degree, and the preset number of iterations is used as the taboo unlocking method.

7. The structural layout evaluation method based on static stability analysis according to claim 6, characterized in that: The multi-objective iterative optimization based on finite element method comprises: A first number of pre-adjustment defects is randomly determined, disturbance optimization is performed, and a first strategy set is determined, wherein the optimization degree of the static stability index is used as the optimization judgment criterion, Randomly determine a second number of pre-adjusted defects, perform disturbance optimization, and determine a second strategy set, wherein the first number and the second number are positive integers greater than or equal to 1 and less than or equal to the total number of defects, and the first number and the second number have no correlation; Iterate and optimize until the convergence condition is met, calibrate the first strategy set, the second strategy set, and finally the Nth strategy set, and select the target optimization strategy.

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