Civil aircraft vertical flight path planning system and planning method thereof

Abstract

The application provides a civil aircraft vertical flight path planning system and a planning method thereof, the planning system comprising an air traffic control center, a ground cloud service, an airborne installed EFB device, an airborne weather radar, an airborne information system, an interconnected information transmission and processing module, and an interconnected flight control system; the planning system and the planning method thereof adopt the interconnected flight control system to receive weather restrictions and air route air traffic control restrictions, and adopt an optimization model combined with an intelligent optimization algorithm to calculate a locally optimal vertical flight path or a globally optimal vertical flight path according to actual flight requirements, thereby greatly improving the flexibility of flight management vertical flight path planning and making it more in line with actual flight conditions. The planned vertical flight path meets the restriction conditions and achieves the shortest flight time, the highest fuel efficiency, or the most balanced cost, thereby greatly saving the actual operation cost.

Description

Technical Field

[0001] This invention relates to the field of civil aircraft interconnected flight control system technology, and in particular to a civil aircraft vertical trajectory planning system and its planning method. Background Technology

[0002] The main task of vertical profile flight management is to optimize the flight path of the aircraft's vertical profile. The main purpose of vertical profile flight path optimization is to reduce fuel costs or shorten flight time during the flight process in order to reduce flight costs. The current method for vertical trajectory planning in airborne flight management involves the pilot setting the performance mode via the control display component before takeoff, selecting the current aircraft performance database and obtaining performance data. The interconnected flight control system presets the flight trajectory based on the performance database and navigation database, calculates and generates the vertical profile flight trajectory using a recommended cost index, and sends the vertical profile parameters to the flight control system to generate corresponding vertical guidance signals. When the aircraft deviates from the predetermined vertical profile, the vertical guidance signals are calculated and corrected to bring the aircraft back to the preset vertical profile. Since the relevant trajectory information is set before takeoff, real-time optimization of the vertical profile cannot be carried out during flight based on the actual aircraft status, flight phase, airspace status, and en-route weather conditions. Furthermore, the trajectory optimization operation does not use advanced optimization algorithm models to perform optimization for the entire flight phase (from takeoff to approach and landing) or for a portion of the flight phase (takeoff, climb, cruise, descent, or approach and landing).

[0003] Current interconnected flight control systems use vertical trajectory planning methods based on pre-set aircraft performance and navigation databases, relying on cost indices input by the pilot. However, with the rapid increase in the number of aircraft, the opening of low-altitude airspace, and activities by other airspace users, there is a growing demand for continuous optimization of vertical trajectories during flight to achieve optimal performance across all or part of the flight phase. Existing vertical paths generated by pre-set cost indices are not necessarily the lowest fuel consumption or shortest flight time paths, leading to increased fuel consumption and longer flight times, resulting in increased operating costs and wasted airspace resources.

[0004] Therefore, if a civil aircraft vertical trajectory planning system and its planning method can be provided, enabling partial or full-flight optimization to be carried out according to the actual flight situation during each flight, in order to meet the increasingly high requirements of airlines for reducing flight costs and aircraft delay time, it will have great market and application prospects. Summary of the Invention

[0005] To address the problems in existing technologies, this invention provides a civil aircraft vertical trajectory planning system and its planning method. By selecting one or more parameter optimization models, utilizing an interconnected flight control system to receive meteorological and en-route air traffic control restrictions, and combining the optimization model with an intelligent optimization algorithm, it calculates the locally optimal or globally optimal vertical trajectory based on actual flight requirements. This significantly improves the flexibility of vertical trajectory planning in flight management, making it more consistent with actual flight conditions. It ensures that the planned vertical trajectory, while meeting the constraints, achieves a comprehensive consideration of factors such as shortest flight time, highest fuel efficiency, or lowest cost index, thereby greatly reducing actual operating costs.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A civil aircraft vertical trajectory planning system, comprising: The air traffic control center generates air traffic control information for aircraft and sends it to the ground cloud service for storage. Ground cloud services are used to receive and store air traffic control information from the air traffic control command center and transmit it to the airborne information system via the ground-to-air data link. Airborne EFB equipment is used by pilots to input flight restriction information that is temporarily generated during flight based on actual conditions. It enhances the pilot's situational awareness of the flight plan through three-dimensional visualization and sends the flight restriction information input by the pilot to the airborne information system through the airborne data link. Airborne weather radar is used to collect real-time weather data along the flight path during flight and transmit the real-time weather data to the airborne information system via an airborne data link. The airborne information system receives air traffic control information from ground cloud services, encodes the air traffic control information, and sends it to the interconnected information transmission and processing module; it receives real-time route weather data from airborne weather radar, encodes the real-time route weather data, and sends it to the interconnected information transmission and processing module; it receives flight restriction information temporarily generated during flight based on actual conditions, input by the pilot from the airborne EFB equipment, encodes the flight restriction information input by the pilot, and sends it to the interconnected information transmission and processing module. The interconnected information transmission and processing module decodes, identifies, and transforms the air traffic control information from the airborne information system, the flight restriction information from the airborne EFB, and the real-time route meteorological data from the airborne meteorological radar. It then generates corresponding airspace mathematical constraints, pilot temporary mathematical constraints, and meteorological mathematical constraints, which are sent to the interconnected flight control system as input constraints for vertical path optimization. Interconnected flight control systems are used for interconnected flight management of aircraft, generating optimal paths for the aircraft's vertical flight path.

[0007] In a preferred embodiment, the interconnected information transmission and processing module includes an interconnected information transmission module, an interconnected information decoding module, and a mathematical constraint generation module. The interconnected information transmission module is used to transmit coded air traffic control information, flight restriction information temporarily generated during flight based on actual conditions, and real-time route weather data. The interconnected information decoding module is used to decode encoded air traffic control command information, flight restriction information temporarily generated during flight based on actual conditions, and real-time route meteorological data, and generate corresponding structured airspace restriction mathematical information, structured pilot restriction mathematical information, and structured meteorological restriction mathematical information. The mathematical constraint generation module is used to generate airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions for use in the vertical path optimization process by corresponding structured airspace constraint mathematical information, structured pilot constraint mathematical information, and structured meteorological constraint mathematical information. This includes constraint models, which comprise air traffic control data models, pilot constraint models, and meteorological constraint models. The air traffic control data model is used to calculate and generate airspace constraint mathematical conditions from the structured airspace constraint mathematical information. The pilot constraint model is used to calculate and generate pilot constraint mathematical conditions from the structured pilot constraint mathematical information. The meteorological constraint model is used to calculate and generate meteorological constraint mathematical conditions from the structured meteorological constraint mathematical information.

[0008] In a preferred embodiment, the airspace restriction mathematical conditions of the air traffic control data model include altitude restrictions at designated waypoints, altitude restrictions in designated airspace, and speed restrictions at designated waypoints or airspace. The speed restrictions include restrictions on the aircraft's vacuum speed, Mach number, and ground speed.

[0009] The specific model is as follows: Altitude restrictions at designated waypoints or airspace:

[0010] Speed ​​limits at designated waypoints or airspace:

[0011] The meteorological limiting mathematical conditions of the meteorological limiting model include the limitation of the aircraft’s vacuum speed and ground speed under the influence of the wind field throughout the flight process or during a specified flight process. The specific model is as follows:

[0012] Where: let ∂ be the true heading, β be the yaw angle, and W s For wind speed, W dThe wind direction is (the angle of clockwise rotation from due north).

[0013] The pilot restriction mathematical conditions of the pilot restriction model include altitude restrictions at designated waypoints, altitude restrictions in designated airspace, and speed restrictions at designated waypoints or airspace. The speed restrictions include restrictions on the aircraft's vacuum speed, Mach number, and ground speed.

[0014] The specific model is as follows: Altitude restrictions at designated waypoints or airspace:

[0015] Speed ​​limits at designated waypoints or airspace: .

[0016] In the preferred embodiment, the interconnected flight control system includes a CDU pilot input module, a performance mode setting module, an aircraft performance acquisition module, an aircraft performance database, a vertical path optimization module, a real-time vertical navigation information acquisition module, a vertical path comparison module, and a vertical path correction module. The CDU pilot input module is used for inputting initial performance parameters and initializing the interconnected flight control system. The performance mode setting module is used to determine the performance mode based on the input content of the CDU pilot input module; The aircraft performance acquisition module is used to read the corresponding flight performance data from the aircraft performance database according to the performance mode determined by the performance mode setting module. The aircraft performance database is used to store flight management performance data, which includes aerodynamic data, engine performance data, takeoff and approach data, weight and balance data, takeoff and landing performance data, climb performance data, cruise performance data, descent performance data, and holding performance data. The vertical path optimization module is used to intelligently optimize the aircraft's vertical trajectory based on the data read from the aircraft performance database by the constraint module and the aircraft performance acquisition module, and generate the aircraft's optimal path as the aircraft's target path. The real-time vertical navigation information acquisition module is used to acquire the aircraft's current real-time navigation path information in real time. The vertical path comparison module is used to compare the real-time navigation path information obtained by the real-time vertical navigation information acquisition module with the target path generated by the vertical path optimization module, and output the comparison result to the vertical path correction module. The vertical path correction module is used to correct the aircraft's trajectory based on the comparison results from the vertical path comparison module, so that the aircraft's trajectory is closer to the target path.

[0017] In a preferred embodiment, the vertical path optimization module includes a constraint model selection module, a target trajectory optimization model module, and an optimal path generation module. The constraint model selection module is used to select one or more corresponding constraint models from the mathematical constraint generation module, and then select one or more corresponding airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions for use by the target trajectory optimization model module. The target trajectory optimization model module is used to calculate the minimum flight time target, the minimum fuel consumption target, or the equilibrium target based on the selected one or more flight phases, and to generate the best performance parameters using an intelligent optimization algorithm. The optimal path generation module is used to generate the optimal path for the aircraft, which serves as the target path for the aircraft.

[0018] In the preferred technical solution, the target trajectory optimization model module includes a minimum flight time model, a minimum fuel consumption model, a comprehensive model, a target trajectory optimization selection module, a flight phase database, a flight phase optimization selection module, and an intelligent optimization algorithm module. The minimum flight time model is used to evaluate the optimal flight time for an aircraft, and its specific model is as follows:

[0019] The minimum fuel consumption model is used to evaluate the optimal fuel consumption for aircraft flight, and its specific model is as follows:

[0020] The comprehensive model is used to evaluate the minimum cost of aircraft flight, and its specific model is as follows:

[0021] Where m is the aircraft mass, g is the acceleration due to gravity, T is the engine thrust, D is the aerodynamic drag, is the energy equation, V is the aircraft speed, SFC is the engine fuel consumption rate, C is the pilot evaluation factor with cruise weighting, ε is the cost per unit cruise distance, and x represents the total range of the aircraft. u Indicates the total climb distance and x d The total descent distance is represented by tcf, the start time of the cruise phase is represented by tci, the end time of the cruise phase is represented by Ei, the initial energy is represented by Ef, the final energy is represented by Eci, the energy at the start of cruise is represented by Ecf, and the energy at the end of cruise is represented by Ecf. The flight phase database is used to store flight phase data for the aircraft's takeoff, climb, cruise, descent, approach and landing. The flight phase optimization selection module is used to select the flight phase that needs to be optimized from the flight phase database; The target trajectory optimization selection module is used to select the minimum flight time model, the minimum fuel consumption model, or a combined model. The intelligent optimization algorithm module is used to calculate the optimal flight parameters based on the genetic annealing algorithm with penalty and elite selection mechanisms, and then calculate the optimal solution of the stage selected by the flight stage optimization selection module and the model selected by the target trajectory optimization model module.

[0022] In the preferred technical solution, the target trajectory optimization selection module can only be selected from the minimum flight time model, the minimum fuel consumption model, and the comprehensive model.

[0023] Another objective of this invention is to provide a method for vertical flight path planning of civil aircraft, comprising the following steps: An air traffic control center generates air traffic control information for the aircraft and sends it to a ground cloud service for storage; the ground cloud service receives and stores the air traffic control information from the air traffic control center and sends it to the airborne information system via a ground-to-air data link; the pilot inputs flight restriction information temporarily generated during flight based on actual conditions using an airborne EFB device, and enhances the pilot's situational awareness of the flight plan through three-dimensional visualization, and sends the pilot-input flight restriction information to the airborne information system via the airborne data link; an airborne weather radar collects real-time route weather data during flight and sends the real-time route weather data to the airborne information system via the airborne data link; the airborne information system receives air traffic control information from the ground cloud service, encodes the air traffic control information, and sends it to an interconnected information transmission and processing module; the airborne information system receives real-time route weather data from the airborne weather radar. The system receives real-time airway meteorological data, encodes it into aeronautical data, and sends it to the interconnected information transmission and processing module. The airborne information system receives flight restriction information temporarily generated during flight based on actual conditions from the pilot, input from the airborne EFB (Airborne Flight Controller) equipment, and encodes this information before sending it to the interconnected information transmission and processing module. The interconnected information transmission and processing module decodes and transforms the air traffic control information from the airborne information system, the flight restriction information from the airborne EFB, and the real-time airway meteorological data from the airborne weather radar, generating corresponding airspace mathematical constraints, pilot temporary mathematical constraints, and meteorological mathematical constraints. These are then sent to the interconnected flight control system as input constraints for vertical path optimization. Based on the initial performance parameters input by the pilot and the vertical path optimization constraints sent from the interconnected flight control system, the interconnected flight control system performs interconnected flight management of the aircraft, generating the optimal path for the aircraft's vertical trajectory.

[0024] In the preferred technical solution, the interconnected flight control system performs interconnected flight management on the aircraft based on the initial performance parameters input by the pilot and the vertical path optimization constraints sent by the interconnected flight control system. The specific steps for generating the optimal path for the aircraft's vertical trajectory are as follows: Step 1: The pilot inputs initial performance parameters and initializes the interconnected flight control system through the CDU pilot input module; Step 2: The performance mode setting module determines the performance mode based on the input from the CDU pilot input module; Step 3: The aircraft performance database acquisition module acquires relevant data from the aircraft performance database; Step 4: The constraint model selection module selects one or more of the corresponding constraint models from the airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions in the constraint generation module. Step 5: The pilot selects the flight phase to be optimized from the flight phase database using the flight phase optimization selection module; Step Six: The pilot selects one of the following models through the target trajectory optimization selection module: minimum flight time model, minimum fuel consumption model, or a combined model. Step 7: The intelligent optimization algorithm module uses a genetic annealing algorithm based on a penalty mechanism and an elite selection mechanism to calculate flight parameters, and then calculates the optimal parameters of the stage selected by the flight stage optimization selection module and the model selected by the target trajectory optimization model module. Step 8: The optimal path generation module uses the selected optimization stage and the selected model generation stage or the global optimal path as the target path for the aircraft. Step 9: The real-time vertical navigation information acquisition module acquires the aircraft's current real-time navigation path information. Step 10: The vertical path comparison module compares the real-time navigation path information with the target path and outputs the comparison result to the vertical path correction module; the vertical path correction module corrects the aircraft's trajectory based on the comparison result of the vertical path comparison module, so that the aircraft's trajectory continuously moves closer to the target path.

[0025] The preferred technical solution, the specific process of step seven is as follows: Step 1: Parameter encoding; Step 2: Initialize the population; Step 3: Algorithm parameter initialization; Step 4: Fitness assessment, assessing population fitness with a penalty mechanism and recording the best individual; Step 5: Determine if the termination condition is met. If yes, proceed to step 6; otherwise, proceed to step 8. Step 6: Input the optimal solution; Step 7: Decode the optimal encoding; Step 8: Selecting and retaining elites; Step 9: Tournament Selection; Step 10: Arithmetic Crossover; Step 11: Gaussian mutation; Step 12: Local search initialization; Step 13: Local iteration judgment. If the local iteration is successful, proceed to step 14; otherwise, proceed to step 21. Step 14: Generate neighborhood solutions; Step 15: Calculate the fitness of the neighborhood solution; Step 16: Calculate the fitness difference; Step 17: Determine the best solution. If the fitness is less than 0, proceed to step 18; otherwise, proceed to step 19. Step 18: Accept the neighborhood solution; Step 19: Accept the inferior solution with probability. If accepted, proceed to step 18; otherwise, keep the current solution unchanged and proceed to step 20. Step 20: Local iterative update, return to step 13; Step 21: Output optimized offspring; Step 22: Generate a new generation of population; Step 23: Annealing and cooling; Step 24: Global Algebra Update.

[0026] Compared with existing technologies, the beneficial effects of the civil aircraft vertical trajectory planning system and planning method of the present invention are: 1. This invention allows pilots to choose from three flight path optimization models, including the minimum flight time model, the minimum fuel consumption model, and the balanced model, and allows pilots to decide on the optimized flight phase, giving them maximum autonomy in flight selection. 2. This invention uses an interconnected flight control system that receives real-time restrictions from weather, air traffic control, and pilots, enabling vertical path optimization to be carried out according to the actual airspace flight conditions, which is closer to the actual flight situation of the aircraft. 3. This invention proposes a comprehensive model calculation method, which introduces pilot evaluation factors during the cruise phase, allowing pilots to increase or decrease the weight of the cruise phase based on actual flight conditions. 4. Based on the intelligent optimization method of interconnected flight management, this invention proposes a genetic annealing algorithm based on a penalty mechanism and an elite selection mechanism to calculate flight parameters, which can calculate the optimal solution for the selected stage and the selected calculation model.

[0027] In summary, this invention provides a vertical trajectory planning method for a civil aircraft interconnected flight control system. By selecting one or more parameter optimization models, utilizing interconnected flight control to receive meteorological and en-route air traffic control restrictions, and combining optimization models with intelligent optimization algorithms, the method calculates locally optimal or globally optimal vertical trajectories based on actual flight requirements. This significantly improves the flexibility of vertical trajectory planning in flight management, making it more consistent with actual flight conditions. It ensures that the planned vertical trajectory, while meeting constraints, achieves a comprehensive consideration of minimizing flight time, maximizing fuel efficiency, or achieving cost equilibrium, thereby greatly reducing actual operating costs. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the architecture of a civil aircraft vertical trajectory planning system according to the present invention.

[0029] Figure 2 This is a schematic diagram of the architecture of the interconnected information transmission and processing module of the present invention.

[0030] Figure 3 This is a schematic diagram of the architecture of the interconnected flight control system of the present invention.

[0031] Figure 4 This is a schematic diagram of the architecture of the vertical path optimization module of the present invention.

[0032] Figure 5 This is a schematic diagram of the architecture of the target trajectory optimization model module of the present invention.

[0033] Figure 6 This is a flowchart illustrating a method for vertical trajectory planning of civil aircraft according to the present invention.

[0034] Figure 7 This is a flowchart illustrating the genetic annealing algorithm based on a penalty mechanism and an elite selection mechanism used in the intelligent optimization algorithm module of this invention. Detailed Implementation

[0035] The relevant terms used in this invention are explained as follows: Airborne EFB (electronic flight bag, usually abbreviated as EFB) equipment.

[0036] CDU (Control Display Unit, often abbreviated as CDU, refers to the input / output device used by pilots to interact with the flight management system).

[0037] Reference Figures 1 to 7 The present invention provides a further description of a civil aircraft vertical trajectory planning system and planning method.

[0038] Example 1

[0039] like Figures 1 to 6 As shown: This invention discloses a civil aircraft vertical trajectory planning system, comprising: (1) Air traffic control center, used to generate air traffic control information for aircraft and send it to ground cloud service for storage; (2) Ground cloud service, used to receive and store air traffic control information from the air traffic control command center and send it to the airborne information system through the ground-to-air data link; (3) Airborne EFB equipment is used for pilots to input flight restriction information that is temporarily generated during flight based on the actual situation, and to increase the pilots' situational awareness of the flight plan through three-dimensional visualization, and to send the flight restriction information input by the pilots to the airborne information system through the airborne data link; (4) Airborne meteorological radar, used to collect real-time route meteorological data during flight and send the real-time route meteorological data to the airborne information system through the airborne data link; (5) The airborne information system receives air traffic control information from the ground cloud service and encodes the air traffic control information before sending it to the interconnected information transmission and processing module; receives real-time route meteorological data from the airborne meteorological radar and encodes the real-time route meteorological data before sending it to the interconnected information transmission and processing module; receives flight restriction information temporarily generated during flight based on actual conditions input by the pilot from the airborne EFB equipment and encodes the flight restriction information input by the pilot before sending it to the interconnected information transmission and processing module. (6) Interconnected information transmission and processing module decodes and identifies the air traffic control information of the airborne information system, the flight restriction information of the airborne EFB and the real-time route meteorological data of the airborne meteorological radar, and generates corresponding airspace mathematical restriction conditions, pilot temporary mathematical restriction conditions and meteorological mathematical restriction conditions, which are then sent to the interconnected flight control system as input for vertical path optimization. (7) Interconnected flight control system, used for interconnected flight management of aircraft and generating the optimal path for the vertical flight path of aircraft.

[0040] In this embodiment, the interconnected information transmission and processing module includes an interconnected information transmission module, an interconnected information decoding module, and a mathematical constraint generation module; The interconnected information transmission module is used to transmit coded air traffic control information, flight restriction information temporarily generated during flight based on actual conditions, and real-time route weather data. The interconnected information decoding module is used to decode encoded air traffic control command information, flight restriction information temporarily generated during flight based on actual conditions, and real-time route meteorological data, and generate corresponding structured airspace restriction mathematical information, structured pilot restriction mathematical information, and structured meteorological restriction mathematical information. The mathematical constraint generation module is used to generate airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions for use in the vertical path optimization process by corresponding structured airspace constraint mathematical information, structured pilot constraint mathematical information, and structured meteorological constraint mathematical information. This includes constraint models, which comprise air traffic control data models, pilot constraint models, and meteorological constraint models. The air traffic control data model is used to calculate and generate airspace constraint mathematical conditions from the structured airspace constraint mathematical information. The pilot constraint model is used to calculate and generate pilot constraint mathematical conditions from the structured pilot constraint mathematical information. The meteorological constraint model is used to calculate and generate meteorological constraint mathematical conditions from the structured meteorological constraint mathematical information.

[0041] The airspace restriction mathematical conditions of the air traffic control data model include altitude restrictions at designated waypoints, altitude restrictions in designated airspace, and speed restrictions at designated waypoints or airspace. The speed restrictions include restrictions on the aircraft's vacuum speed, Mach number, and ground speed.

[0042] The specific model is as follows: Altitude restrictions at designated waypoints or airspace:

[0043] Speed ​​limits at designated waypoints or airspace:

[0044] The meteorological constraint mathematical conditions of the meteorological constraint model include the constraints on the influence of wind field on vacuum speed and ground speed during the entire flight process or a specified flight process. The specific model is as follows:

[0045] Where: let ∂ be the true heading, β be the yaw angle, and W s For wind speed, W d The wind direction is (the angle of clockwise rotation from due north).

[0046] The pilot restriction mathematical conditions of the pilot restriction model include altitude restrictions at designated waypoints, altitude restrictions in designated airspace, and speed restrictions at designated waypoints or airspace. The speed restrictions include restrictions on the aircraft's vacuum speed, Mach number, and ground speed.

[0047] The specific model is as follows: Altitude restrictions at designated waypoints or airspace:

[0048] Speed ​​limits at designated waypoints or airspace: .

[0049] The interconnected flight control system includes a CDU pilot input module, a performance mode setting module, an aircraft performance acquisition module, an aircraft performance database, a vertical path optimization module, a real-time vertical navigation information acquisition module, a vertical path comparison module, and a vertical path correction module. The CDU pilot input module is used for inputting initial performance parameters and initializing the interconnected flight control system. The performance mode setting module is used to determine the performance mode based on the input content of the CDU pilot input module; The aircraft performance acquisition module is used to read the corresponding flight performance data from the aircraft performance database according to the performance mode determined by the performance mode setting module. The aircraft performance database is used to store flight management performance data, which includes aerodynamic data, engine performance data, takeoff and approach data, weight and balance data, takeoff and landing performance data, climb performance data, cruise performance data, descent performance data, and holding performance data. The vertical path optimization module is used to intelligently optimize the aircraft's vertical trajectory based on the data read from the aircraft performance database by the constraint module and the aircraft performance acquisition module, and generate the aircraft's optimal path as the aircraft's target path. The real-time vertical navigation information acquisition module is used to acquire the aircraft's current real-time navigation path information in real time. The vertical path comparison module is used to compare the real-time navigation path information obtained by the real-time vertical navigation information acquisition module with the target path generated by the vertical path optimization module, and output the comparison result to the vertical path correction module. The vertical path correction module is used to correct the aircraft's trajectory based on the comparison results from the vertical path comparison module, so that the aircraft's trajectory is closer to the target path.

[0050] The vertical path optimization module includes a constraint model selection module, a target trajectory optimization model module, and an optimal path generation module. The constraint model selection module is used to select one or more corresponding constraint models from the mathematical constraint generation module, and then select one or more corresponding airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions for use by the target trajectory optimization model module. The target trajectory optimization model module is used to calculate the minimum flight time target, the minimum fuel consumption target, or the equilibrium target based on the selected one or more flight phases, and to generate the best performance parameters using an intelligent optimization algorithm. The optimal path generation module is used to generate the optimal path for the aircraft, which serves as the target path for the aircraft.

[0051] The target trajectory optimization model module includes a minimum flight time model, a minimum fuel consumption model, a comprehensive model, a target trajectory optimization selection module, a flight phase database, a flight phase optimization selection module, and an intelligent optimization algorithm module; The minimum flight time model is used to evaluate the optimal flight time for an aircraft, and its specific model is as follows:

[0052] The minimum fuel consumption model is used to evaluate the optimal fuel consumption for aircraft flight, and its specific model is as follows:

[0053] The comprehensive model is used to evaluate the minimum cost of aircraft flight, and its specific model is as follows:

[0054] Where m is the aircraft mass, g is the acceleration due to gravity, T is the engine thrust, D is the aerodynamic drag, is the energy equation, V is the aircraft speed, SFC is the engine fuel consumption rate, C is the pilot evaluation factor with cruise weighting, ε is the cost per unit cruise distance, and x represents the total range of the aircraft. u Indicates the total climb distance and x d The total descent distance is represented by tcf, the start time of the cruise phase is represented by tci, the end time of the cruise phase is represented by Ei, the initial energy is represented by Ef, the final energy is represented by Eci, the energy at the start of cruise is represented by Ecf, and the energy at the end of cruise is represented by Ecf. The flight phase database is used to store flight phase data for the aircraft's takeoff, climb, cruise, descent, approach and landing. The flight phase optimization selection module is used to select the flight phase that needs to be optimized from the flight phase database; The target trajectory optimization selection module is used to select the minimum flight time model, the minimum fuel consumption model, or a comprehensive model; the target trajectory optimization selection module can only be applied to one of the minimum flight time model, the minimum fuel consumption model, and the comprehensive model.

[0055] The intelligent optimization algorithm module is used to calculate the optimal flight parameters based on the genetic annealing algorithm with penalty and elite selection mechanisms, and then calculate the optimal solution of the stage selected by the flight stage optimization selection module and the model selected by the target trajectory optimization model module.

[0056] like Figure 6 or Figure 7 As shown, the working principle of the civil aircraft vertical trajectory planning system of the present invention is as follows: The air traffic control center generates air traffic control information for the aircraft and sends it to the ground cloud service for storage. The ground cloud service receives and stores the air traffic control information from the air traffic control center and sends it to the airborne information system via a ground-to-air data link. Pilots input flight restriction information generated temporarily during flight based on actual conditions through airborne EFB devices, and enhance their situational awareness of the flight plan through 3D visualization. The input flight restriction information is then sent to the airborne information system via the airborne data link. The airborne weather radar collects real-time en-route weather data during flight and sends it to the airborne information system via the airborne data link. The airborne information system receives air traffic control information from the ground cloud service, encodes the information, and sends it to the interconnected information transmission and processing module. The airborne information system receives real-time en-route weather data from the airborne weather radar and processes the data. After being encoded, the airborne data is sent to the interconnected information transmission and processing module. The airborne information system receives flight restriction information temporarily generated during flight based on actual conditions from the pilot input from the airborne EFB device, and encodes the pilot's input flight restriction information before sending it to the interconnected information transmission and processing module. The interconnected information transmission and processing module decodes, identifies, and transforms the air traffic control information from the airborne information system, the flight restriction information from the airborne EFB, and the real-time route meteorological data from the airborne weather radar, generating corresponding airspace mathematical constraints, pilot temporary mathematical constraints, and meteorological mathematical constraints, which are then sent to the interconnected flight control system as input constraints for vertical path optimization. Based on the initial performance parameters input by the pilot and the vertical path optimization constraints sent by the interconnected flight control system, the interconnected flight control system performs interconnected flight management of the aircraft and generates the optimal path for the aircraft's vertical trajectory.

[0057] The interconnected flight control system performs interconnected flight management on the aircraft based on the initial performance parameters input by the pilot and the vertical path optimization constraints sent by the interconnected flight control system. The specific steps for generating the optimal path for the aircraft's vertical trajectory are as follows: Step 1: The pilot inputs initial performance parameters and initializes the interconnected flight control system through the CDU pilot input module; Step 2: The performance mode setting module determines the performance mode based on the input from the CDU pilot input module; Step 3: The aircraft performance database acquisition module acquires relevant data from the aircraft performance database; Step 4: The constraint model selection module selects one or more of the corresponding constraint models from the airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions in the constraint generation module. Step 5: The pilot selects the flight phase to be optimized from the flight phase database using the flight phase optimization selection module; Step Six: The pilot selects one of the following models through the target trajectory optimization selection module: minimum flight time model, minimum fuel consumption model, or a combined model. Step 7: The intelligent optimization algorithm module uses a genetic annealing algorithm based on a penalty mechanism and an elite selection mechanism to calculate flight parameters, and then calculates the optimal parameters of the stage selected by the flight stage optimization selection module and the model selected by the target trajectory optimization model module. Step 8: The optimal path generation module uses the selected optimization stage and the selected model generation stage or the global optimal path as the target path for the aircraft. Step 9: The real-time vertical navigation information acquisition module acquires the aircraft's current real-time navigation path information. Step 10: The vertical path comparison module compares the real-time navigation path information with the target path and outputs the comparison result to the vertical path correction module; the vertical path correction module corrects the aircraft's trajectory based on the comparison result of the vertical path comparison module, so that the aircraft's trajectory continuously moves closer to the target path.

[0058] The intelligent optimization combination algorithm in the target trajectory optimization model module of step seven mentioned above is as follows: I. The minimum time model is as follows: Define the equation of motion along the trajectory direction and the force balance perpendicular to the trajectory direction, where m is the aircraft mass, g is the acceleration due to gravity, T is the engine thrust, and D is the aerodynamic drag. Let θ be the angle of attack, θ be the track angle, L be the lift, h be the altitude, and V be the vacuum speed.

[0059]

[0060]

[0061] Define the energy equation E s The following is an example, where V is the velocity in vacuum, g is the acceleration due to gravity, and h is the height:

[0062] Differentiating with respect to Es, we get:

[0063] Substituting into the equation of motion, we get:

[0064] When the flight path angle and angle of attack are small, sinθ is approximately 0 and cosγ is approximately 1, which simplifies to:

[0065] Therefore, the minimum time model is:

[0066] In discrete computing, the energy range can be divided into N small segments, and in some embodiments, it can be approximated as follows:

[0067] in This represents the residual power (TD) V obtained by looking up the optimal envelope at the midpoint of the k-th energy interval.

[0068] II. The minimum fuel consumption model is as follows: Define the fuel weight change rate as:

[0069] SFC stands for engine fuel consumption rate. After introducing the energy equation, the formula is rewritten as:

[0070] In some embodiments, discrete calculations can also be used, dividing the energy range into N smaller segments, which can then be approximated as:

[0071] III. The air traffic control data model is Air Control: That is, altitude restrictions at designated waypoints; altitude restrictions in designated airspace; and speed restrictions at designated waypoints or airspace, including airspeed, Mach number, and ground speed.

[0072] IV. The aforementioned integrated model: Define the cost function Cost, where F 耗油 Fuel consumption for a complete flight, CI is the cost index, and T is the fuel consumption. 耗时 Fuel consumption for a complete flight

[0073] Under the capability state equation, since the cruise phase often lasts the longest and consumes the most resources during the entire flight path, a cruise weight pilot evaluation factor c is introduced to increase the relevant proportion. ε is the cost per unit cruise distance, and x represents the aircraft's total range. u and x d These represent the total climb and descent distances, respectively. tcf and tci represent the start and end times of the cruise phase, respectively. Ei represents the initial energy, Ef represents the final energy, and Eci and Ecf represent the energy at the start and end of the cruise phase.

[0074]

[0075] V. The wind model is as follows: Because wind speed affects ground speed:

[0076] Let ∂ be the true heading, θ be the track angle, β be the yaw angle, Ws be the wind speed, and Wd be the wind direction (the angle of clockwise rotation from true north). Then, according to the wind speed model:

[0077] Under the influence of the wind model, the vacuum velocity in the minimum time model and the minimum fuel consumption model is replaced with the ground velocity under the influence of wind, and the model is optimized.

[0078] VI. The target trajectory optimization model module ultimately adopts Trajectory Optimization, that is: A weighted average trajectory optimization model TO is introduced, under the constraints of the air traffic control model:

[0079] Where φ, μ, and λ are the weights for selecting the model, which can only be 0 or 1, and only one of them can be 1.

[0080] VII. The intelligent optimization algorithm is as follows: The intelligent optimization algorithm described is a genetic annealing algorithm based on a penalty mechanism and an elite selection mechanism. The main algorithm design idea is as follows: using a genetic algorithm as the main framework for global search, and after mutation operations in the genetic algorithm, performing simulated annealing for local search to enhance local optimization capabilities. A penalty mechanism is introduced: constraints (such as aircraft performance limitations, airspace restrictions, etc.) are added to the objective function as penalty terms. An elite selection mechanism: a certain number of optimal individuals are retained in each generation and directly enter the next generation to avoid the loss of excellent solutions.

[0081] That is, the specific algorithm steps of step seven are as follows: Step 1: Parameter encoding; Step 2: Initialize the population; Step 3: Algorithm parameter initialization; Step 4: Fitness assessment, assessing population fitness with a penalty mechanism and recording the best individual; Step 5: Determine if the termination condition is met. If yes, proceed to step 6; otherwise, proceed to step 8. Step 6: Input the optimal solution; Step 7: Decode the optimal encoding; Step 8: Selecting and retaining elites; Step 9: Tournament Selection; Step 10: Arithmetic Crossover; Step 11: Gaussian mutation; Step 12: Local search initialization; Step 13: Local iteration judgment. If the local iteration is successful, proceed to step 14; otherwise, proceed to step 21. Step 14: Generate neighborhood solutions; Step 15: Calculate the fitness of the neighborhood solution; Step 16: Calculate the fitness difference; Step 17: Determine the best solution. If the fitness is less than 0, proceed to step 18; otherwise, proceed to step 19. Step 18: Accept the neighborhood solution; Step 19: Accept the inferior solution with probability. If accepted, proceed to step 18; otherwise, keep the current solution unchanged and proceed to step 20. Step 20: Local iterative update, return to step 13; Step 21: Output optimized offspring; Step 22: Generate a new generation of population; Step 23: Annealing and cooling; Step 24: Global Algebra Update.

[0082] To further explain this step, this application example uses selecting the minimum time model as the optimization objective, and the steps are illustrated as follows: Step 1: Parameter Encoding Using real number encoding, the individual = [H, Ma] Step 2: Initialize the population Individual 1: [9000, 0.75] Individual 2: [9200, 0.76] Individual 3: [9500, 0.77] Individual 4: [9800, 0.78] Step 3: Algorithm parameter initialization Current iteration g=1 Initial temperature T=100 Cooling coefficient α = 0.95 Local iteration L=2 Elite retention E=1 Step 4 Fitness assessment (time calculation using energy method) For each individual case, the following fixed parameters are used: Aircraft mass m = 70000 kg The acceleration due to gravity is g = 9.81 m / s². 2 Net thrust TD = 20000N The initial unit energy is 10000m 2 / s 2 The target unit energy is 64000m 2 / s 2 To simplify the calculation, this calculation uses a steady climb single-segment calculation (N=1). but: Fitness of individual 1: t≈2.04h Individual fitness: t≈2.01h Individual fitness: t≈1.98h Individual fitness 4: t≈1.96h The current global optimum is: [9800, 0.78], t = 1.96h Step 5: Termination Condition Determination If g=1≤maximum iterations, do not terminate; jump to step 8. Step 8: Elite Selection and Retention Fitness ranking: 4 < 3 < 2 < 1 Elite Individual: [9800, 0.78], Reserved Step 9: Tournament Selection Remove the elites, remaining: 1, 2, 3 Select parent generation: 2, 3 Step 10: Arithmetic Crossover Parent generation: [9500, 0.77], [9200, 0.76] w=0.5 Offspring: [9350, 0.765] Step 11: Gaussian Mutation With a slight perturbation, the offspring becomes: [9600, 0.79] Step 12: Local search initialization The current solution is x = [9600, 0.79]. Calculation t1 = Energy method time ≈ 1.93h k=0 Step 13: Local Iteration Judgment k=0<2 Continue Step 14: Generate neighborhood solutions x=[9700,0.80] Step 15: Calculate the fitness of the neighborhood solution t2≈1.91h Step 16: Calculate the difference Δt = t2 - t1 = 1.91 - 1.93 = -0.02 Step 17: Determining the best solution Better, Acceptable Step 18: Accept neighborhood solutions x=[9700,0.80], t≈1.91h Step 19: Do not execute Step 20: k=1 Step 13: k=1<2 Continue Step 14: Neighborhood solution [10500, 0.85] Step 15: t2≈1.80h Step 16: Δt = 1.80 - 1.91 = -0.11 Step 17: Better, Accept Step 18: Update to [10500, 0.85], t ≈ 1.80h Step 19: Do not execute Step 20: k=2 Step 13: k=2 Exit local search Step 21: Output optimized offspring [10500,0.85],t≈1.80h Step 22: Generate a new generation of population Elite [9800, 0.78] Optimize the offspring [10500, 0.85] Step 23: Cool down to T=95 Step 24: g=2 The algorithm ends, and the optimized offspring is [10500, 0.85], t min ≈1.80h The above is just an illustrative example of an application. In actual algorithm execution, there will be a larger population, more generations, and more iteration steps to continuously approach the optimal parameters.

[0083] The algorithm steps for the minimum fuel consumption model, the integrated model, and the minimum time model are the same. The only difference is that the minimum fuel consumption model and the integrated model are used to calculate the fitness in step three. Therefore, they will not be described again here.

[0084] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. It should be noted that any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A civil aircraft vertical trajectory planning system, characterized in that: It includes: The air traffic control center generates air traffic control information for aircraft and sends it to the ground cloud service for storage. Ground cloud services are used to receive and store air traffic control information from the air traffic control command center and transmit it to the airborne information system via the ground-to-air data link. Airborne EFB equipment is used by pilots to input flight restriction information that is temporarily generated during flight based on actual conditions. It enhances the pilot's situational awareness of the flight plan through three-dimensional visualization and sends the flight restriction information input by the pilot to the airborne information system through the airborne data link. Airborne weather radar is used to collect real-time weather data along the flight path during flight and transmit the real-time weather data to the airborne information system via an airborne data link. The airborne information system receives air traffic control information from ground cloud services and encodes the air traffic control information before sending it to the interconnected information transmission and processing module. It receives real-time route weather data from airborne weather radar, encodes the real-time route weather data into aviation data, and sends it to the interconnected information transmission and processing module; it receives flight restriction information temporarily generated during flight based on actual conditions from the pilot input from the airborne EFB equipment, encodes the flight restriction information input by the pilot, and sends it to the interconnected information transmission and processing module. The interconnected information transmission and processing module decodes, identifies, and transforms the air traffic control information from the airborne information system, the flight restriction information from the airborne EFB, and the real-time route meteorological data from the airborne meteorological radar. It then generates corresponding airspace mathematical constraints, pilot temporary mathematical constraints, and meteorological mathematical constraints, which are sent to the interconnected flight control system as input constraints for vertical path optimization. Interconnected flight control systems are used for interconnected flight management of aircraft, generating optimal paths for the aircraft's vertical flight path.

2. The civil aircraft vertical trajectory planning system according to claim 1, characterized in that: The interconnected information transmission and processing module includes an interconnected information transmission module, an interconnected information decoding module, and a mathematical constraint generation module. The interconnected information transmission module is used to transmit coded air traffic control information, flight restriction information temporarily generated during flight based on actual conditions, and real-time route weather data. The interconnected information decoding module is used to decode encoded air traffic control command information, flight restriction information temporarily generated during flight based on actual conditions, and real-time route meteorological data, and generate corresponding structured airspace restriction mathematical information, structured pilot restriction mathematical information, and structured meteorological restriction mathematical information. The mathematical constraint generation module is used to generate the airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions used in the vertical path optimization process by corresponding the structured airspace constraint mathematical information, structured pilot constraint mathematical information, and structured meteorological constraint mathematical information. The system includes a constraint model, which comprises an air traffic control data model, a pilot constraint model, and a meteorological constraint model. The air traffic control data model is used to calculate and generate airspace constraint mathematical conditions from structured airspace constraint mathematical information. The pilot constraint model is used to calculate and generate pilot constraint mathematical conditions from structured pilot constraint mathematical information. The meteorological constraint model is used to calculate and generate meteorological constraint mathematical conditions from structured meteorological constraint mathematical information.

3. The civil aircraft vertical trajectory planning system according to claim 2, characterized in that: The airspace restriction mathematical conditions of the air traffic control data model include altitude restrictions at designated waypoints, altitude restrictions in designated airspace, and speed restrictions at designated waypoints or airspace. The speed restrictions include restrictions on the aircraft's airspeed, Mach number, and ground speed. The meteorological limiting mathematical conditions of the meteorological limiting model include the limitation of the aircraft’s vacuum speed and ground speed under the influence of the wind field throughout the flight process or during a specified flight process. The pilot restriction mathematical conditions of the pilot restriction model include altitude restrictions at designated waypoints, altitude restrictions in designated airspace, and speed restrictions at designated waypoints or airspace. The speed restrictions include restrictions on the aircraft's vacuum speed, Mach number, and ground speed.

4. A civil aircraft vertical trajectory planning system according to claim 3, characterized in that: The interconnected flight control system includes a CDU pilot input module, a performance mode setting module, an aircraft performance acquisition module, an aircraft performance database, a vertical path optimization module, a real-time vertical navigation information acquisition module, a vertical path comparison module, and a vertical path correction module. The CDU pilot input module is used for inputting initial performance parameters and initializing the interconnected flight control system. The performance mode setting module is used to determine the performance mode based on the input content of the CDU pilot input module; The aircraft performance acquisition module is used to read the corresponding flight performance data from the aircraft performance database according to the performance mode determined by the performance mode setting module. The aircraft performance database is used to store flight management performance data, which includes aerodynamic data, engine performance data, takeoff and approach data, weight and balance data, takeoff and landing performance data, climb performance data, cruise performance data, descent performance data, and holding performance data. The vertical path optimization module is used to intelligently optimize the aircraft's vertical trajectory based on the data read from the aircraft performance database by the constraint module and the aircraft performance acquisition module, and generate the aircraft's optimal path as the aircraft's target path. The real-time vertical navigation information acquisition module is used to acquire the aircraft's current real-time navigation path information in real time. The vertical path comparison module is used to compare the real-time navigation path information obtained by the real-time vertical navigation information acquisition module with the target path generated by the vertical path optimization module, and output the comparison result to the vertical path correction module. The vertical path correction module is used to correct the aircraft's trajectory based on the comparison results from the vertical path comparison module, so that the aircraft's trajectory is closer to the target path.

5. A civil aircraft vertical trajectory planning system according to claim 4, characterized in that: The vertical path optimization module includes a constraint model selection module, a target trajectory optimization model module, and an optimal path generation module. The constraint model selection module is used to select one or more corresponding constraint models from the mathematical constraint generation module, and then select one or more corresponding airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions for use by the target trajectory optimization model module. The target trajectory optimization model module is used to calculate the minimum flight time target, the minimum fuel consumption target, or the equilibrium target based on the selected one or more flight phases, and to generate the best performance parameters using an intelligent optimization algorithm. The optimal path generation module is used to generate the optimal path for the aircraft, which serves as the target path for the aircraft.

6. A civil aircraft vertical trajectory planning system according to claim 5, characterized in that: The target trajectory optimization model module includes a minimum flight time model, a minimum fuel consumption model, a comprehensive model, a target trajectory optimization selection module, a flight phase database, a flight phase optimization selection module, and an intelligent optimization algorithm module; The minimum flight time model is used to evaluate the optimal flight time for an aircraft, and its specific model is as follows: ； The minimum fuel consumption model is used to evaluate the optimal fuel consumption for aircraft flight, and its specific model is as follows: ； The comprehensive model is used to evaluate the minimum cost of aircraft flight, and its specific model is as follows: ； Where m is the aircraft mass, g is the acceleration due to gravity, T is the engine thrust, D is the aerodynamic drag, is the energy equation, V is the aircraft speed, SFC is the engine fuel consumption rate, C is the pilot evaluation factor with cruise weighting, ε is the cost per unit cruise distance, and x represents the total range of the aircraft. u Indicates the total climb distance and x d The total descent distance is represented by tcf, the start time of the cruise phase is represented by tci, the end time of the cruise phase is represented by Ei, the initial energy is represented by Ef, the final energy is represented by Eci, the energy at the start of cruise is represented by Ecf, and the energy at the end of cruise is represented by Ecf. The flight phase database is used to store flight phase data for the aircraft's takeoff, climb, cruise, descent, approach and landing. The flight phase optimization selection module is used to select the flight phase that needs to be optimized from the flight phase database; The target trajectory optimization selection module is used to select the minimum flight time model, the minimum fuel consumption model, or a combined model. The intelligent optimization algorithm module is used to calculate the optimal flight parameters based on the genetic annealing algorithm with penalty and elite selection mechanisms, and then calculate the optimal solution of the stage selected by the flight stage optimization selection module and the model selected by the target trajectory optimization model module.

7. A civil aircraft vertical trajectory planning system according to claim 6, characterized in that: The target trajectory optimization selection module can only be applied to one of the following models: minimum flight time model, minimum fuel consumption model, and comprehensive model.

8. A method for planning the vertical trajectory of a civil aircraft, characterized in that: It includes the following steps: The air traffic control center generates air traffic control information for the aircraft and sends it to the ground cloud service for storage. The ground cloud service receives and stores the air traffic control information from the air traffic control center and sends it to the airborne information system via a ground-to-air data link. Pilots input flight restriction information generated temporarily during flight based on actual conditions through airborne EFB devices, and enhance their situational awareness of the flight plan through 3D visualization. The input flight restriction information is then sent to the airborne information system via the airborne data link. The airborne weather radar collects real-time en-route weather data during flight and sends it to the airborne information system via the airborne data link. The airborne information system receives air traffic control information from the ground cloud service, encodes the information, and sends it to the interconnected information transmission and processing module. The airborne information system receives real-time en-route weather data from the airborne weather radar and processes the data. After being encoded, the airborne data is sent to the interconnected information transmission and processing module. The airborne information system receives flight restriction information temporarily generated during flight based on actual conditions from the pilot input from the airborne EFB device, and encodes the pilot's input flight restriction information before sending it to the interconnected information transmission and processing module. The interconnected information transmission and processing module decodes, identifies, and transforms the air traffic control information from the airborne information system, the flight restriction information from the airborne EFB, and the real-time route meteorological data from the airborne weather radar, generating corresponding airspace mathematical constraints, pilot temporary mathematical constraints, and meteorological mathematical constraints, which are then sent to the interconnected flight control system as input constraints for vertical path optimization. Based on the initial performance parameters input by the pilot and the vertical path optimization constraints sent by the interconnected flight control system, the interconnected flight control system performs interconnected flight management of the aircraft and generates the optimal path for the aircraft's vertical trajectory.

9. The method for vertical trajectory planning of a civil aircraft according to claim 8, characterized in that: The interconnected flight control system performs interconnected flight management on the aircraft based on the initial performance parameters input by the pilot and the vertical path optimization constraints sent by the interconnected flight control system. The specific steps for generating the optimal path for the aircraft's vertical trajectory are as follows: Step 1: The pilot inputs initial performance parameters and initializes the interconnected flight control system through the CDU pilot input module; Step 2: The performance mode setting module determines the performance mode based on the input from the CDU pilot input module; Step 3: The aircraft performance database acquisition module acquires relevant data from the aircraft performance database; Step 4: The constraint model selection module selects one or more of the corresponding constraint models from the airspace constraint mathematical conditions, pilot constraint mathematical conditions, and meteorological constraint mathematical conditions in the constraint generation module. Step 5: The pilot selects the flight phase to be optimized from the flight phase database using the flight phase optimization selection module; Step Six: The pilot selects one of the following models through the target trajectory optimization selection module: minimum flight time model, minimum fuel consumption model, or a combined model. Step 7: The intelligent optimization algorithm module uses a genetic annealing algorithm based on a penalty mechanism and an elite selection mechanism to calculate flight parameters, and then calculates the optimal parameters of the stage selected by the flight stage optimization selection module and the model selected by the target trajectory optimization model module. Step 8: The optimal path generation module uses the selected optimization stage and the selected model generation stage or the global optimal path as the target path for the aircraft. Step 9: The real-time vertical navigation information acquisition module acquires the aircraft's current real-time navigation path information. Step 10: The vertical path comparison module compares the real-time navigation path information with the target path and outputs the comparison result to the vertical path correction module; The vertical path correction module corrects the aircraft's trajectory based on the comparison results from the vertical path comparison module, ensuring that the aircraft's trajectory continuously approaches the target path.

10. A method for planning the vertical trajectory of a civil aircraft according to claim 9, characterized in that: The specific process of step seven is as follows: Step 1: Parameter encoding; Step 2: Initialize the population; Step 3: Algorithm parameter initialization; Step 4: Fitness assessment, assessing population fitness with a penalty mechanism and recording the best individual; Step 5: Determine if the termination condition is met. If yes, proceed to step 6; otherwise, proceed to step 8. Step 6: Input the optimal solution; Step 7: Decode the optimal encoding; Step 8: Selecting and retaining elites; Step 9: Tournament Selection; Step 10: Arithmetic Crossover; Step 11: Gaussian mutation; Step 12: Local search initialization; Step 13: Local iteration judgment. If the local iteration is successful, proceed to step 14; otherwise, proceed to step 21. Step 14: Generate neighborhood solutions; Step 15: Calculate the fitness of the neighborhood solution; Step 16: Calculate the fitness difference; Step 17: Determine the best solution. If the fitness is less than 0, proceed to step 18; otherwise, proceed to step 19. Step 18: Accept the neighborhood solution; Step 19: Accept the inferior solution with probability. If accepted, proceed to step 18; otherwise, keep the current solution unchanged and proceed to step 20. Step 20: Local iterative update, return to step 13; Step 21: Output optimized offspring; Step 22: Generate a new generation of population; Step 23: Annealing and cooling; Step 24: Global Algebra Update.

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