120 results about "Flight dynamics" patented technology

The invention discloses a dual-ring active-disturbance-rejection trajectory tracking control method for a four-rotor unmanned aerial vehicle, and the method comprises the steps: representing a dynamic coupling effect of the unmanned aerial vehicle caused by the load mass change and dynamic center-of-gravity shift through a six-degree-of-freedom flight dynamic model containing an asymmetric inertia matrix; an outer ring position control loop and an inner ring attitude control loop are constructed on the basis of an active disturbance rejection controller, and the following control cycles are executed in real time on the basis of integrating an extended state observer: the outer ring position control loop generates a position control signal and an attitude expected angle according to an expected track; the inner loop attitude control loop generates a control quantity for driving the unmanned aerial vehicle according to the attitude expected angle, and the two loops cooperatively work through decoupling logic to realize expected trajectory tracking; estimating and compensating unmodeled dynamics and external interference of the unmanned aerial vehicle in real time through the extended state observer; and dynamically adjusting parameters of the active-disturbance-rejection controller by adopting a particle swarm optimization algorithm.

The invention discloses a machine learning-based flight wheel block removal time prediction method, and relates to the technical field of flight prediction, and the method comprises the steps: collecting flight preorder state data, airport resource distribution data and meteorological data in real time, and generating an original data set through multi-source heterogeneous data fusion; constructing spatio-temporal features including a preorder flight delay propagation chain, a stand-vehicle conflict energy matrix and a meteorological attenuation factor, and screening and optimizing a feature set through distribution drift detection; training and verifying the Bayesian depth quantile regression model, and outputting a prediction result with a confidence interval; and combining the airport Internet of Things positioning feedback optimization feature set and parameters to generate a prediction deviation diagnosis report. According to the method, a preorder flight delay propagation chain and a stand-vehicle conflict energy matrix are constructed, flight dynamics, resource allocation and weather attenuation factors are embedded into a unified spatial-temporal feature space, and the problem of feature information loss caused by data isolation is solved.

The invention discloses an end-to-end obstacle avoidance method considering flight dynamics of a fixed-wing unmanned aerial vehicle, and the method comprises the steps: constructing a multi-source data synchronous collection module, and obtaining a monocular depth image and inertial navigation state data which are aligned in time sequence; an enhanced visual perception coding module is designed, and spatial position information of a tiny obstacle is reserved at the tail end of feature extraction through an asymmetric convolution strategy and a parallel spatial attention mechanism; constructing a state fusion and time sequence reasoning module, performing long and short time sequence modeling on the multi-modal features by using an encoder with a causal mask mechanism, and outputting potential decision variables; and constructing a kinematics constraint trajectory generation module, and mapping the neural network output into a three-dimensional control trajectory conforming to flight mechanics limitation. The problems that spatial information of a traditional convolutional neural network is seriously lost, an end-to-end model easily generates an illusion trajectory exceeding a physical limit and the like are solved, and the flight safety and robustness of the fixed-wing unmanned aerial vehicle in a complex low-altitude environment are remarkably improved.

The invention relates to the technical field of flight safety of civil aircrafts, in particular to a flight trajectory prediction method under the condition of air high-speed target hood perforation, which comprises the following steps: acquiring calculation coefficient parameter data of a target flight dynamics model, establishing a trajectory prediction framework based on a three-degree-of-freedom target flight dynamics model and target real-time flight data; the method comprises the following steps: performing numerical simulation on a flow field of a hood perforation area through fluid mechanics analysis software to obtain speed field and pressure field data, establishing a hood perforation flow field pneumatic analysis model by adopting a high-order polynomial fitting method, and calculating Mach number and pressure distribution after hood perforation; dynamically updating aerodynamic coefficient data and an aerodynamic parameter database; the speed and pressure distribution data are introduced into the three-degree-of-freedom target flight dynamics model for registration updating, a prediction track is obtained, the prediction precision is improved by 30%-50%, and especially under the condition of a large angle of attack, the prediction error is controlled to be within 5% from 20% or above.

The invention relates to the technical field of artificial intelligence and aviation income management, in particular to an AI-driven flight dynamic pricing and intelligent bargaining system and an implementation method thereof. Comprising a passenger intention analysis module, an intention order hanging module, an income management docking module, an intelligent bargaining engine module, a transaction feedback module, a third-party task entrusting module and a block chain evidence storage module. Pricing is accurately matched with passenger budget, time preference and service requirements, an intelligent bargaining engine supports multiple rounds of interaction, passengers can trigger re-pricing by adjusting conditions such as time range and shipping space selection, and a third-party task price-withstanding mechanism provides a cost reduction channel for the passengers and improves the efficiency of the passengers. Block chain evidence storage ensures that bargaining records, transaction data and price information cannot be tampered, and the problems that in traditional transactions, data tracing is difficult, and dispute handling is complex are solved.

The invention relates to a tilt rotorcraft semi-physical simulation system and method, and relates to the technical field of wind tunnel flight test semi-physical simulation. Based on the initialized system with the test parameters set, six-component balance load, wind speed and attitude data are collected in real time, and the collected key physical data are filtered and then sent to the flight simulation subsystem; the flight simulation subsystem carries out calculation based on a flight dynamics model, a rotor wing power model, a control instruction preprocessing model and the received data and outputs an actuation instruction; the actuator receives an actuation instruction and drives the aircraft model, and the airborne sensor feeds back new attitude data to form a control closed loop; the flight simulation subsystem sends state data to the 3D visual simulation module in real time to realize synchronization of control and visual; in this way, the stable state under the combination of different tilting angles and flight speeds is recorded, and a tilting transition corridor is obtained through fitting. Therefore, simulation precision, test safety and iteration efficiency are taken into consideration, and fused semi-physical simulation is formed.

The application discloses a helicopter flight dynamics model parameter error correction method, comprising the following steps: S1, parameterizing the discrete form of helicopter aerodynamic data to obtain multiple aerodynamic parameters and form a flight dynamics parameterization model; S2, performing trimming error analysis on the parameterization model, determining each main input parameter through sensitivity analysis, and using a trimming error value matrix and a trimming error fitting coefficient matrix about the forward flight speed to represent the model trimming error; and S3, taking the trimming error value matrix and the trimming error fitting coefficient matrix as the input of a neural network to identify each error. The application parameterizes the discrete aerodynamic data to obtain the flight dynamics parameterization model, makes the parameters more explicit, adopts the input parameter error cross combination mode to calculate and generate training samples, and identifies the error of each main input parameter by using the neural network, so that the calculation cost is effectively reduced, and the correction efficiency and accuracy are improved.

The invention provides a civil aircraft safety perception method and system based on virtual flight, and relates to the technical field of aircraft safety perception. A dynamic and hierarchical three-dimensional wind shear field model is constructed through space-time alignment and fusion of multi-source meteorological data; deep coupling of wind disturbance and aircraft dynamic response is realized based on a small disturbance theory and a flight dynamics model; continuous and dynamic quantification of risks is realized by combining and analyzing flight parameters and a safety threshold value dynamically adjusted based on wind disturbance intensity and utilizing multi-parameter risk level weighted integration; according to the method, the risk coefficient is coupled with the three-dimensional terrain and the virtual flight trajectory, hierarchical color mapping is adopted to carry out visual space visualization, and a complete closed loop from environment modeling to risk early warning is formed, so that the identification accuracy and timeliness of the flight risk in the wind shear environment are greatly improved, and the scientificity and practicability of security situation awareness are enhanced.

The invention discloses an intelligent ticket business recommendation method and system based on dynamic flight data, and relates to the technical field of intelligent ticket business recommendation, the intelligent ticket business recommendation method based on the dynamic flight data comprises the following specific steps: step 1, based on basic data, associated data and derivative data contained in a dynamic flight, establishing a dynamic ticket business recommendation model; the method comprises the steps of collecting multi-dimensional dynamic flight data and completing data preprocessing, 2, constructing user portrait data by integrating user real-time preferences and basic demands, and dynamically updating the user portrait data based on fixed duration or behavior recognition, and 3, based on the real-time user portrait and flight dynamic data as input, adopting a random forest algorithm to identify the flight data in real time. And step 4, setting a comprehensive recommendation score based on the feature scores, determining flight ticket business data to be matched, and screening data with high matching degree with the user as recommended ticket business data, and by capturing user demand changes in real time, it is ensured that recommended contents are highly matched with user demands.

A method for controlling anti-skid braking in civil aircraft involves constructing an anti-skid braking model and flight dynamics and kinematics models of the aircraft to analyze the forces acting on the aircraft system and obtain the corresponding forces and torques. For the anti-skid braking system, a BSMC controller is designed to control the braking coefficient μ. Brake This invention controls the braking force to ultimately control the anti-skid braking system of civil aircraft. It uses a backstepping slip mode controller (BSMC) to control the aircraft's braking commands, ensuring the system maintains the optimal slip ratio during braking, maximizing braking efficiency, reducing wheel wear, and minimizing the cost of the aircraft's braking system.

The invention discloses a parachute flight performance prediction method based on follow-up coupling flow field analysis, and the method is suitable for a parafoil and a traditional round parachute. Parachute flight flow field aerodynamic characteristics and flight dynamic characteristics are coupled by using a body-attached dynamic grid and a self-adaptive flow field boundary technology, real-time changes of a parachute streaming flow field along with body motion are accurately reflected, and the attitude, the speed and the flight trajectory of the parachute are automatically solved and obtained. According to the method, on one hand, real-time aerodynamic characteristics and motion characteristics of the parafoil are coupled, the coupling influence of flight attitude speed change on aerodynamic force and aerodynamic torque of the parafoil is reflected, and the calculation precision is guaranteed; and meanwhile, the change of the streaming flow field of the parachute system is decoupled into the change of the relative incoming flow and the change of the posture, so that the redundancy of flow field grids and the complex grid reconstruction are avoided, and the simulation calculation efficiency is improved.

The invention belongs to the technical field of synthetic aperture radars, and relates to a bistatic SAR receiver flight path planning method, electronic equipment and a storage medium. The method comprises the following steps: establishing motion models of a transmitter, a moving target and a receiver; establishing a three-dimensional proportional guidance model, and establishing a motion differential equation of the receiver driven by the enhanced proportional guidance law as a guidance flight path; establishing a mixed integer nonlinear programming model taking the optimal approximation guide flight path as a target function, and taking an imaging constraint, a guide terminal constraint, a flight dynamics constraint and a system communication constraint as constraint conditions; and solving the mixed integer nonlinear programming model to obtain the optimal flight path of the receiver meeting the guidance and imaging dual constraints. According to the method, the small miss distance guidance precision of the maneuvering target can be ensured in the terminal guidance stage; the terminal guidance performance and the SAR imaging quality are both considered, the feasible solution space is greatly expanded, and the feasibility and optimization performance of trajectory planning under complex constraint conditions are improved.

The invention provides an atmospheric data analysis method based on observability analysis, belongs to the field of aircraft navigation, guidance and control, and aims at solving the problem that the precision of traditional atmospheric data measurement is reduced under the condition of a complex flow field or a sensor fault. In the prior art, due to lack of strict theoretical support, estimation errors and convergence problems may occur in a transonic stage. According to the method, an atmospheric data state space model is established through flight dynamics, and atmospheric data estimation is carried out by adopting an extended Kalman filter based on the model; in the estimation process, observability analysis is executed to verify the reliability of an estimation result; and finally, optimizing the system model according to an analysis result. According to the method, the dependence of an existing method on an empirical model is reduced, the convergence and the stability of an estimation result are ensured, and the adaptability and the robustness of a system in a complex environment are remarkably improved.

The invention provides an unmanned aerial vehicle supervision system based on an electronic license plate. The system comprises a terminal layer, a network layer, a service platform and a supervision platform. Wherein the terminal layer comprises at least one unmanned aerial vehicle provided with an electronic license plate, and the electronic license plate is used for collecting flight dynamic data of the unmanned aerial vehicle in real time and supervising the unmanned aerial vehicle according to the flight dynamic data and electronic fence information issued by the supervision platform; the network layer is used for reporting the flight dynamic data to a service platform and synchronizing the electronic fence information to each electronic license plate; the business platform is used for performing data analysis on the flight dynamic data and reporting the flight dynamic data to the supervision platform; and the supervision platform is used for formulating electronic fence information, generating a flight path according to the flight dynamic data, and supervising the unmanned aerial vehicle according to the flight path. According to the invention, the unmanned aerial vehicle can be better supervised.

This invention discloses an aircraft flight status identification method and system based on ADS-B, comprising: acquiring ADS-B data of the aircraft in real time and caching the ADS-B data in a high-speed cache database; extracting the latest ADS-B data points of the aircraft from the high-speed cache database at set time intervals, and storing multiple consecutively extracted latest ADS-B data points into a fixed-length queue of a preset length to form a temporal ADS-B data sequence; calculating estimated parameters for status determination by combining the aircraft's flight dynamic data with preset geospatial information; and identifying the current flight stage of the aircraft through a state machine model based on the temporal ADS-B data sequence and the estimated parameters, wherein the current flight stage includes one of taxiing, takeoff, climb, cruise, descent, approach, and landing. The method and system of this application improve the accuracy, continuity, and real-time performance of flight status identification.

The invention belongs to the technical field of unmanned aerial vehicle control, and provides an unmanned aerial vehicle linear flight control method and device. The method comprises the following steps: collecting flight state parameters and environment interference parameters of an unmanned aerial vehicle, wherein the flight state parameters comprise at least one of a three-dimensional position, a flight speed, a course angle, a lateral offset distance and an attitude angle; according to the flight state parameters and the environment interference parameters, constructing an unmanned aerial vehicle linear flight dynamics model, linear flight constraint conditions and a fusion reward function; a linear flight simulation environment constructed based on the unmanned aerial vehicle linear flight dynamics model; based on a reinforcement learning algorithm, the linear flight constraint condition and the fusion reward function, performing interactive training on the unmanned aerial vehicle and the linear flight simulation environment to determine a linear flight control strategy; and controlling the unmanned aerial vehicle to fly linearly according to the linear flight control strategy. According to the invention, high-precision, high-stability and energy-saving autonomous linear flight control can be realized, dependence on an accurate model is significantly reduced, and complex environmental interference is effectively coped with.

The invention discloses a method for dynamically correcting departure time based on flights, which comprises the following steps: acquiring running state information and time parameters of a target flight in real time, and calculating corrected departure time according to a preset initial calculation rule based on the running state information and the time parameters after judging that preset calculation triggering time is reached; presetting a trigger event for updating the corrected departure time, monitoring the change of the running state information of the flight, and recalculating and updating the corrected departure time according to an updating calculation rule corresponding to the trigger event after judging that the trigger event is met; and outputting the calculated or updated corrected departure time. According to the method, the most appropriate preparation time of the flight can be automatically calculated and updated in real time along with the change of the flight state, so that the problems that manual estimation is inaccurate and the plan cannot be changed are effectively solved, the waiting time of an airplane on the ground is shortened, the flight punctuality rate can be improved, and the airport operation is smoother and more efficient.

The invention belongs to the technical field of flight dynamics modeling in aircraft design, and particularly relates to a dynamics modeling method for an overwater tilting wing aircraft. Comprising the following steps: step 1, modeling a wing section based on a blade element theory, dividing an unmanned aerial vehicle into three parts including a propeller, the wing and a fuselage, and carrying out an experiment or CFD calculation to obtain aerodynamic data; 2, geometric parameters of a wing micro-section, a control surface, a propeller and a wing tilting shaft are obtained; 3, calculating wing aerodynamic force, propeller aerodynamic force and fuselage aerodynamic force according to the aerodynamic force data and the geometric parameters; 4, hydrodynamic force is calculated, and the hydrodynamic force comprises buoyancy, inertia force and wave disturbance force.

The application discloses a kind of cloud end collaborative aviation work load distribution method and system, belong to aviation transport technical field;Including: collecting flight dynamics, personnel qualification, physiological state and environmental data;Adaptive threshold denoising in sliding window median, uniform timestamp, based on fuzzy time window association fusion, construct load evaluation dataset;Multi-modal load prediction model fusion time series network, graph convolution network based on historical co-protection frequency normalized edge weight and attention mechanism, modeling inter-post load conduction, predict future load;With load variance, task balance, fatigue risk and cost as target, introduce adaptive crossover mutation optimization scheduling;Using cumulative prospect theory to evaluate fatigue, multidimensional weighted calculation basic score and deviation, distinguish the prospect value mapping level of income loss domain;According to the flow of flight dynamic adjustment safety threshold, over-limit early warning intervention.

The invention relates to the technical field of aviation, and provides an aircraft intrinsic parameter online resolving method based on steady-state weight optimization. The method comprises the following steps: firstly, constructing a flight dynamics model and defining a to-be-solved intrinsic parameter set; secondly, adopting a steady-state weight optimization architecture, minimizing an error between an output estimated value of a measurement system model and an actual sensor data vector through iterative optimization, and directly updating an estimated value of an intrinsic parameter set; and finally, calculating process convergence is automatically judged based on statistical convergence characteristics of a parameter estimation sequence, and a result is output. According to the method, engineering-level precision eigenparameter calculation can be realized under the condition that calculation resources are limited, and key technical support is provided for performance degradation evaluation and efficiency management of aircrafts.

The invention discloses an approximate iteration analytic calculation method for a flight trajectory of a hypersonic flight vehicle, which comprises the following steps of: firstly, establishing a gliding flight dynamics mode of the hypersonic flight vehicle, and ignoring lateral motion to obtain a longitudinal plane dynamics model in a linear matrix differential equation form; secondly, according to the characteristics of different types of flight trajectories, performing targeted simplification on a linear matrix differential equation, and analyzing the characteristics of a jump gliding trajectory and a balanced gliding trajectory through matrix eigenvalues; then, on the basis of the quasi-equilibrium gliding condition, lift-drag ratio characteristics of the equilibrium gliding track are analyzed; then, an approximate dynamic model in a short-time period is established, and a flight path analytical expression in the short-time period is obtained; and finally, based on the flight path analytical calculation expression in the short-time period, proposing a flight path approximate iteration analytical calculation process in the long-time period. The method is simple in structure and easy for engineering realization, and has a relatively large popularization and application space.

The application discloses an airport bus network optimization method and system integrating air traffic control information, and the method comprises the following steps: acquiring the geographical range of the airport bus operation area, passenger reservation demand and passenger online car-hailing order data generated by the influence of flight dynamic changes according to the air traffic control information; determining all airport bus station positions in the airport bus operation area; establishing a target function according to passenger travel time cost and airport bus operation cost, and establishing constraint conditions according to the maximum number of passengers served by the airport bus starting station, the service level of the airport bus service, the lower limit and the upper limit of the time window in which the passenger expects the airport bus to arrive; and solving a reservation response bus scheduling model to obtain an airport bus scheduling scheme. Under the condition of flight changes, the number of passengers taking the airport bus and their destinations can be known in advance, the operation strategy can be quickly adjusted, and the vehicle scheduling can be optimized, so that the waiting time and in-vehicle time of passengers can be effectively saved, and the passenger satisfaction under the condition of flight changes can be improved.

The embodiment of the specification provides a kind of based on quasi-static electric quantity discrete electric aircraft reachable domain evaluation method and system, wherein, method includes: the quasi-static dimension reduction conversion of electric aircraft dynamics model, according to quasi-static hypothesis, simplify electric aircraft dynamics equation, it is decoupled as horizontal plane kinematics equation and push resistance balance and lift weight balance equation constraint, reduce state quantity dimension, obtain dimension reduction flight dynamics model;The electric quantity discrete conversion of dimension reduction flight dynamics model, the form of relative to time dynamics equation is converted into relative to electric quantity consumption value, determines simulation interval and discrete grid;Based on the dimension reduction flight dynamics model, by setting roll angle numerical sequence, numerical integration simulation is carried out on the simulation interval and discrete grid, and the horizontal plane maneuvering reachable domain boundary of electric aircraft is obtained.

The application discloses a kind of based on bluetooth beacon equipment automatic collection flight guarantee node data method and system, method includes: in the each guarantee node area of flight ground guarantee process, respectively install bluetooth beacon equipment, each bluetooth beacon equipment is associated with the corresponding guarantee node area by identity coding;For guarantee personnel configuration terminal equipment, terminal equipment is configured to when entering or leaving the signal coverage boundary of any bluetooth beacon equipment, automatically obtain the identity coding of this bluetooth beacon equipment and generate trigger data upload to background system;Background system is in real time to interface flight dynamic information system, according to the trigger data received determination corresponding guarantee node area, and associate guarantee node area current matching flight information and guarantee task information.The application realizes the full automation collection and real-time matching of flight guarantee node time data by the dynamic interaction of bluetooth beacon equipment and terminal equipment, significantly improves data accuracy and guarantee efficiency.

The application relates to the technical field of administration and supervision, and discloses a pilot multi-dimensional capability collaborative evaluation method based on a multi-modal heterogeneous graph and decoupling prediction, which comprises the following steps: acquiring multi-modal original data flow in an evaluation task; loading a standard operation procedure knowledge base and converting the same into a logical reference graph; constructing a heterogeneous information graph model integrating causal logic; calculating manifold deviation values between the model and the logical reference graph, modulating node weights on the basis of the manifold deviation values to generate enhanced feature flow; separating the enhanced feature flow into independent dimension-specific representation vectors by using a decoupling prediction system; and outputting an evaluation result based on preset weights. The application embeds standard operation procedure constraints into the bottom layer of a graph model, forces the system to learn the causal mapping between operation behaviors and supervision standards, and eliminates interference between physiological signals and flight dynamics characteristics.

The invention provides an abnormal behavior detection method and system based on flight mission context awareness, and is applied to the technical field of data processing. The method comprises the following steps: processing flight dynamic data and task protocol data of an unmanned aerial vehicle, obtaining a task type by analyzing a MASSIONITEM field in a task protocol, and generating a dynamic tag; combining the GPS positioning data with normalized mutual information and random forest importance score to screen task sensitive features, and generating a task related feature subset; processing the task related feature subsets based on a random forest model, training an exclusive classification model for each task type, and generating an exclusive classification model of each type of tasks; and predicting the real-time flight state data of the unmanned aerial vehicle based on the exclusive classification model of each task to obtain probability distribution of each task type, performing judgment according to a set threshold, and generating an unmanned aerial vehicle abnormal behavior judgment result.

The invention is suitable for the technical field of unmanned aerial vehicle parachute opening, and particularly relates to an emergency parachute opening method and system.The method comprises the steps that a task area of an unmanned aerial vehicle is delimited, a plurality of standby landing point positions are selected, signal equipment sets are created, and each standby landing point position corresponds to one signal equipment set; the signal equipment group is composed of a normally-on group and a flicker group, edits a light coding rule and is embedded into the flicker group; the method comprises the following steps: acquiring flight power data of an unmanned aerial vehicle, judging whether the flight power data is abnormal or not according to a preset evaluation rule, and if so, utilizing a down-looking camera pre-integrated in the unmanned aerial vehicle; collecting image data of a ground area, and traversing a normally-on group; according to the method, the emergency landing point and the target height are determined, the aerodynamics principle can be utilized, the unmanned aerial vehicle drifts with the help of wind power in the falling process and approaches the standby landing point position to the maximum extent, the landing deviation is reduced, and the parachute landing safety and precision are further enhanced.

The invention discloses an unmanned aerial vehicle flight dynamic monitoring method and system based on a three-dimensional map, and relates to the technical field of unmanned aerial vehicle monitoring. The method comprises the following steps: acquiring a three-dimensional map of a target area and low-altitude airspace control requirements, and constructing a low-altitude three-dimensional partition model for describing allowed activities of an unmanned aerial vehicle; historical flight data are collected, comprehensive heat values of the partition units are calculated through a multi-factor weighted evaluation model, and a three-dimensional heat map is generated; defining a layout area, and solving an optimal layout scheme by adopting a multi-objective optimization algorithm by taking the maximization of the weighted total coverage amount and the minimization of the monitoring point number as optimization objectives; monitoring equipment is arranged according to the scheme, and three-dimensional dynamic monitoring of the target area is achieved. According to the method, the problems of multiple monitoring blind areas, unreasonable resource allocation, low monitoring efficiency and the like in a traditional method are effectively solved, and refined and intelligent management of airspace resources is realized.

The application discloses a kind of fuel consumption optimal aerodynamic auxiliary deorbiting high-efficiency prediction-correction guidance methods, belong to aerospace field, including establishing spacecraft aerodynamic auxiliary deorbiting flight dynamics model, and the impulse maneuver model required after spacecraft enters atmosphere, into target orbit, decoupling extraction is carried out in dynamics model simplified longitudinal plane motion equation and makes variable substitution, convert independent variable into energy form variable, obtain the mapping relationship of flight state such as roll control variable and flight path angle, and trajectory characteristic is planned based on fuel consumption optimal aerodynamic auxiliary deorbiting flight path angle profile, the analytical expression of guidance instruction is deduced, three-stage guidance scheme is designed, and high-efficiency prediction-correction guidance is realized.The application uses the above method, can carry out high-efficiency prediction-correction guidance in the aerodynamic auxiliary deorbiting task scene that condition is significantly different, reflect the flexibility and adaptability of method, can provide effective technical support for spacecraft maneuvering orbit transfer mission.

This invention provides a convex optimization design method and system for eVTOL based on power kit selection, belonging to the field of vertical takeoff and landing aircraft design technology. The convex optimization design method includes: obtaining the parameters of the power kit and continuous flight dynamic parameters; constructing aerodynamic models, load characteristic models, battery discharge models, and efficiency models for the eVTOL cruise phase based on the parameters to determine constraints; constructing a convex optimization objective function that minimizes energy consumption per unit range based on the models; solving the convex optimization objective function using the interior-point method to obtain optimal weights and continuous parameters; and obtaining the optimal power kit and mass parameters of each system based on the constraints and optimal weights. This invention achieves simultaneous optimization of discrete power kit selection and continuous parameters under complex constraints, significantly improving optimization accuracy while meeting the strict safety and performance constraints of the entire eVTOL flight profile.