CN116466750A

CN116466750A - Aircraft vertical trajectory prediction and optimization method based on combined model

Info

Publication number: CN116466750A
Application number: CN202310518658.0A
Authority: CN
Inventors: 郑起彪; 齐林; 高磊; 陈祺
Original assignee: China Aeronautical Radio Electronics Research Institute
Current assignee: China Aeronautical Radio Electronics Research Institute
Priority date: 2023-05-09
Filing date: 2023-05-09
Publication date: 2023-07-21

Abstract

The invention discloses an aircraft vertical trajectory prediction and optimization method based on a combined model, which initializes the state parameters of the current position of an aircraft; according to the judgment logic of the vertical flight phase, the current vertical flight phase of the aircraft is obtained, and the vertical track of the whole flight process is calculated segment by segment according to the processing logic of each vertical flight phase; based on the flight characteristics of each vertical flight stage and the proportion of each vertical flight stage in the whole flight process, the calculation accuracy and the calculation efficiency are evaluated and analyzed, and a method of selectively using a performance database model and a first principle model for different flight stages is used for forming an optimal combined model, so that the prediction and optimization of the track parameters of the full-flight vertical section of the aircraft from a take-off airport or the current position to a destination airport or a standby airport are realized. The method can effectively improve the calculation precision of vertical track prediction and optimization, and provides the aircraft state information of each subsequent route point prediction of the flight plan with higher reliability.

Description

Aircraft vertical trajectory prediction and optimization method based on combined model

Technical Field

The invention relates to a vertical track prediction and optimization method of a flight management system. More particularly, the invention relates to a combined model-based aircraft vertical trajectory prediction and optimization method.

Background

With the progress of globalization and the vigorous development of global economy, the air transportation industry of countries around the world has also been developed more rapidly. With the continuous density of air lines and the gradual increase of the number of flights, the flying flow of the airspace is continuously increasing, and the phenomenon of airspace congestion is increasingly prominent. In order to cope with the contradiction between the current situation of shortage of airspace resources and the development requirement of civil aviation, a management mode based on 4D track operation is an effective solution method for dredging a complex airspace with dense flow, and a vertical track prediction and optimization method of an airplane is a core technology for solving the problem.

At present, most aircrafts are provided with a flight management system, so that the aircrew can be effectively helped to realize a plurality of flight tasks such as flight planning, comprehensive navigation, track prediction, flight guidance, performance calculation and the like, and the track prediction can be divided into horizontal track prediction and vertical track prediction, wherein the vertical track prediction and optimization function is an important subfunction of the flight management system. Based on the future flight intention of the aircraft, according to the horizontal flight plan and various aircraft states at the beginning of the vertical trajectory prediction, a certain vertical section integration step length is used, the state at the end of the last integration is taken as the state at the beginning of the next integration, the aircraft is periodically subjected to rapid simulated flight, the vertical trajectory prediction function can calculate a complete 4D flight trajectory along the specified flight plan, the vertical trajectory is continuous from the current position of the take-off airport or the aircraft to the destination airport, and a series of space points are defined from the current position of the take-off airport or the aircraft to the destination airport, wherein each point is defined by geographic position, altitude and time. The vertical trajectory prediction function predicts information such as the flight phase, remaining flight distance, estimated arrival time, speed, altitude, remaining fuel on board, total weight, etc. of each subsequent waypoint in the flight plan, and includes calculated vertical event points, i.e., pseudo waypoints, such as T/C points and T/D points.

The vertical trajectory is optimized to meet certain mission objectives while taking into account aircraft performance constraints, pilot input constraints, and civil airspace flight rules. Vertical trajectory optimization, also known as performance optimization, can optimize the aircraft's altitude profile, speed profile, and thrust profile and minimize the total flight time, fuel consumption, or total flight cost. The optimum flight profile is a compromise between time and fuel costs, and the cost index is typically used to represent the result of this compromise, with the cost index input generally varying from 0 to 999, with minimum fuel consumption corresponding to a cost index of 0, and an increase in the cost index value resulting in an increase in range speed and a change in the vertical trajectory of the aircraft. At a suitable cost index, the increased fuel cost will be offset by the reduced time cost. The aviation industry is constantly striving to reduce the pollution emission generated by fuel cost and fuel consumption, and the fuel consumption is directly proportional to the generated pollution amount, so that the vertical track optimization function is also an important solution for reducing environmental emission, and can effectively help to slow down the greenhouse effect.

The vertical trajectory prediction result calculated by the vertical trajectory prediction and optimization function and the optimal flight trajectory depend not only on the optimization index but also on the mathematical model for predicting the performance of the aircraft, so it is very important and necessary to build the mathematical model of the aircraft close to the real flight. Methods of mathematically modeling aircraft generally include methods based on performance database models and first principles models. The performance database is typically stored in a nonvolatile memory of the aircraft, the data of which is presented in discrete form, typically in a data table, polynomial or other convenient way for representing the data, and stores aerodynamic data, engine data and performance data of the aircraft, and the performance database model accesses the performance database according to specific data query conditions and outputs the desired results by interpolation calculations. The first principle model is usually to calculate the required flight performance data in real time based on the basic equation of flight dynamics of each flight phase by using the original model parameters such as lift, resistance, engine thrust and the like. The first sexual principle model is directly from the established basic physical law, does not depend on means such as a historical experience model, parameter fitting and the like, and the data calculation result is continuously changed, so that the interpolation calculation of the relative performance database model obviously has the advantage of higher calculation precision; however, the calculation process of the first principle model may involve iterative or recursive logic, and introduces more calculation steps, thus having the disadvantage of relatively longer calculation period.

For practical engineering application, comprehensive evaluation and analysis are required to be carried out on calculation accuracy and calculation efficiency, the compromise between calculation accuracy and calculation efficiency is fully considered in the method, the attribute of each required performance parameter is fully analyzed, the method of a first principle model and a performance database model is selectively used for different flight stages according to the influence degree of each performance parameter in track prediction and performance calculation, and the method of the first principle model is selected as the processing method of the main flight stage in the vertical track prediction and optimization process, so that an optimal combined model is formed, the calculation accuracy can be effectively improved, the calculation efficiency is not seriously influenced, and the level of the vertical track prediction and optimization is integrally improved.

Disclosure of Invention

The invention aims to provide an aircraft vertical trajectory prediction and optimization method based on a combined model, which fully considers the compromise between calculation precision and calculation efficiency, selectively uses a first principle model and a performance database model for different flight phases, improves the calculation precision of vertical trajectory prediction and optimization based on the optimal combined model without seriously affecting the calculation efficiency of the process, periodically predicts future flight states in the flight process, provides prompt information with higher reliability, can effectively reduce the flight cost, increases the profit of an airline company, lightens the workload of a flight unit, and can improve the economy, comfort and safety of flight based on reference data.

The invention aims at realizing the following technical scheme:

an aircraft vertical trajectory prediction and optimization method based on a combined model comprises the following steps:

s101, initializing state parameters of the current position of the aircraft;

s102, acquiring a vertical flight stage of the aircraft according to judgment logic of the vertical flight stage, and executing from step S103 if the aircraft is in the pre-flight and take-off stages; if the climbing stage is in, starting execution from step S104; if the vehicle is in the cruising phase, starting from step S105; if in the descending stage, starting execution from step S109; if in the advanced stage, starting from step S110;

s103, processing vertical track prediction in a take-off stage by adopting a performance database model;

s104, processing vertical track prediction of the climbing navigation segment by adopting a first principle model;

s105, processing the vertical track prediction of the cruising flight segment by adopting a first principle model;

s106, when cruise flight processing is performed, if the flight plan is found to be changed, the step 107 is performed, and otherwise, the step 109 is performed;

s107, judging whether a descending bottom point exists, if not, entering a step 110, and if yes, entering a step 108;

S108, constructing a descent path;

s109, processing vertical track prediction of the descending navigation section by adopting a first principle model;

s110, processing the vertical track prediction in the approaching stage by adopting a performance database model.

S111, if the fly-away stage is activated, adopting a performance database model to process the vertical track prediction in the fly-away stage, otherwise, entering a step S113;

s112, processing the vertical track prediction of the spare descent route by adopting a performance database model;

s113, optimizing the vertical flight profile of the whole process based on the vertical 4D track and the optimization index generated by the vertical track prediction of each stage.

Preferably, in S102, the determination logic of the vertical flight phase determines according to the air-ground state, the guidance mode, the distance of the current position from the destination airport, and the relationship between the current altitude and the cruising altitude.

Preferably, in S103, the take-off stage is regarded as an integral stage, integral calculation is performed once according to the height integral step length, unconsumed parts of time, fuel oil and distance are added into initial values of state parameters, and route points falling into the integral stage are subjected to interpolation inquiry from a performance database, so as to determine vertical 4D track sections of each route point in the take-off stage.

Preferably, in S104, a climbing stage is composed of a plurality of navigation segments, including: an initial climbing stage meeting airport speed limits; accelerating from the speed limited by the airport speed to a planned table speed corresponding to a climbing speed mode or a climbing accelerating section generated due to the speed constraint of the waypoint; the aircraft climbs at a constant planned speed until reaching a climbing equal speed section at a crossing height; at the height higher than the crossing height, climbing the equal Mach number climbing section with constant Mach number until reaching the cruising height; it is also possible to include cruise flat flights generated due to altitude constraints of waypoints or altitude of airport speed limits;

predicting the vertical track of the climbing leg, and sequentially processing each leg falling into the climbing stage; when vertical track prediction is carried out on any section of the climbing stage, vertical integral section processing is carried out on the sections, if a plurality of integral sections are involved in one section, the sections are retracted to the section termination position when the sections are terminated in one integral section, so that the horizontal section and the vertical section are mutually coupled; calculating the variation of time, distance, oil consumption and height in one integration section based on a complex first sex principle model, adopting a height integration step length or a time integration step length according to the variation of the climbing rate of the airplane, and continuously carrying out the integration process until the prediction reaches a climbing vertex; the vertical trajectory prediction takes into account speed constraints, altitude constraints, time constraints and airport speed constraints of waypoints, while taking into account acceleration during climb, which are prioritized over predicted climb vertical profiles when waypoint altitude constraints are encountered as part of the vertical flight plan.

Preferably, in S105, a cruising phase is composed of a plurality of voyages, including: a cruise acceleration section for climbing speed to cruise speed; cruise segments of equal table speed or mach number; a step climbing section and a step descending section; a cruise deceleration section that decelerates from a cruise speed to a descent speed;

the vertical track prediction in the cruising stage sequentially processes each navigation segment falling into the cruising stage; when vertical track prediction is carried out on any section of the navigation section in the cruising stage, vertical integral section processing is carried out on the navigation section, the navigation section is retracted to the end position of the navigation section when the navigation section is ended in one integral section, and the horizontal section and the vertical section are mutually coupled; the cruising fuel flow in one integration section is calculated based on a complex first sex principle model, any one of three integration steps of weight, distance and time is adopted, and then the variation of time, distance and fuel consumption in one integration step is calculated, and the integration process is continued until the prediction reaches the descending peak.

Preferably, in S108, the descent path is divided into a slow path section and a geometric path section, the slow path section is constructed by calculating the cruising altitude from the descent bottom point in the direction opposite to the flight based on the slow thrust or the near slow thrust and the speed plan for optimizing the operation, and determining the position point from the cruising altitude to the descent stage in advance; the geometric path segment is constructed based on altitude constraints, speed constraints, airport altitude limits, and flight path angle constraints.

Preferably, in S109, the descending stage is composed of a plurality of navigation segments, including: an equal Mach number descent segment for flying according to the Mach number of the descent schedule; an equal-table-speed descending section for flying according to the table speed of the descending plan; a descent acceleration segment generated by decelerating from a planned table speed corresponding to the descent speed mode to a speed limited by the airport speed or due to the waypoint speed constraint; a descending deceleration section; and continuing to descend to the constant-speed section at which the approach stage begins according to the speed limit of the airport; it is also possible to include cruise flat flights generated due to altitude constraints of waypoints or altitude of airport speed limits;

the method comprises the steps that vertical track prediction of a descending leg sequentially processes each leg falling into the descending leg, vertical integral section processing is conducted on the legs when vertical track prediction is conducted on any leg of the descending leg, the legs are retracted to a leg termination position when the legs are terminated in one integral section, and a horizontal section and a vertical section are mutually coupled; calculating the variation of time, distance, oil consumption and height in one integration section based on a complex first sex principle model, and adopting a height integration step length, wherein the integration process is continued until the prediction reaches the starting point of the approaching stage; the vertical trajectory prediction takes into account speed constraints, altitude constraints, time constraints and airport speed constraints of waypoints, as well as deceleration procedures during descent, when waypoint altitude constraints are encountered, these constraints take precedence over the predicted descent vertical profile.

Preferably, in S110, the approach phase is divided twice according to the altitude interval, that is, the approach phase is regarded as a plurality of product segments, and the waypoints falling into the product segments determine the vertical track predicted value thereof by using an interpolation method.

Preferably, in S112, the vertical trajectory prediction of the standby landing route considers two types of standby landing and direct flight, and determines the vertical flight phase to be included in the standby landing flight plan according to the standby landing flight plan and the standby landing cruising altitude, and the whole standby landing flight plan calculates the time, distance, fuel oil, altitude variation of the standby landing route and the prediction information of the standby landing airport by adopting a performance database model.

The invention has the beneficial effects that:

a) The invention provides a combined model-based high-precision vertical trajectory prediction and optimization method for an aircraft, which fully considers an atmospheric air temperature model and various constraint and limiting conditions, has higher fitting degree of the predicted vertical trajectory and the real flight trajectory of the aircraft, improves the calculation precision of the vertical trajectory prediction and optimization based on the optimal combined model, does not seriously influence the calculation efficiency of the process, and periodically predicts future flight states in the flight process, provides the aircraft state information of each subsequent flight path point prediction in the flight plan with higher reliability, can effectively help a flight unit to make a decision, and improves the flight safety. Accurate prediction information is beneficial to the advanced arrangement of empty pipe control, and the use efficiency of an airspace can be effectively improved.

b) The invention provides a combined model-based high-precision vertical trajectory prediction and optimization method for an aircraft, which can continuously optimize a speed profile, a height profile and a thrust profile of the whole flight process based on certain optimization indexes, can effectively reduce the flight cost, increase the profit of an airline company, lighten the workload of a flight unit and can improve the economy, the comfort and the safety of the flight based on reference data.

Drawings

FIG. 1 is a top level logic flowchart for controlling the overall vertical trajectory prediction process of the present invention.

FIG. 2 is a low-level logic flow diagram of a next level for controlling leg processing in accordance with the present invention.

Fig. 3 is a schematic view of a typical 4D vertical flight profile and an example of a flight phase according to the present invention.

FIG. 4 is a schematic illustration of a vertical section of a climb taking into account waypoint altitude constraints and speed constraints, as presented herein.

Fig. 5 is a schematic illustration of a cruising vertical section including a planned step and an optimal step, according to the present invention.

Fig. 6 is a schematic view of the descent path of the present invention.

Fig. 7 is a schematic diagram of the region division of uniform nature into individual integration intervals given by the present invention.

Detailed Description

The invention is described in further detail below with reference to the drawings and examples.

Referring to fig. 1, the method for predicting and optimizing the vertical trajectory of an aircraft based on a combined model according to the embodiment includes the following steps:

s101, initializing state parameters of the current position of the airplane. To initiate the vertical trajectory prediction and optimization function, the values of the state parameters of the required integration, including the necessary prerequisite data and data that can improve accuracy, must be initialized to reflect the aircraft state at the beginning of each vertical trajectory prediction.

The initialized state parameters include horizontal flight plan data, human-machine interface input data, sensor data, navigation data, and other computing data, etc. The horizontal flight plan data comprises main flight plan and backup flight plan leg data; the man-machine interface input data mainly comprise data such as cruising altitude, zero fuel weight, cost index, speed modes selected in three flight stages of climbing, cruising and descending, performance coefficient and the like; the sensor data mainly comprise actually measured wind and temperature data; the navigation data comprise current position, air pressure correction height, standard atmospheric height and other data; other calculated data include initial position and altitude, total distance to the destination airport taking into account the circular arc transition between legs, system time, total fuel weight, total aircraft weight, etc., taking into account the difference between calculated data when the current leg is active and inactive.

Starting from the current position of the aircraft, the prediction process will accumulate modifications to these variables until the integration process ends. An integration step of vertical trajectory prediction is defined as an integration segment, i.e. an increment unit, each increment unit typically consisting of four basic parameters whose values are updated at the beginning and end of each prediction integration segment, the prediction integration segment being defined as an increment unit or interval that can be predicted. The initial conditions are established at the beginning of the integration period, and the vertical trajectory prediction establishes the integration period termination conditions or end conditions. The vertical trajectory consists of a series of such integration segments connected end to end. The termination condition of one product segment is the initial condition of the next product segment. The four basic parameters are:

t=duration, unit generally taking seconds(s)

W=total aircraft weight, in general pounds (lbs)

H=height, unit generally takes feet (ft)

X=distance to destination airport, units generally take the sea (nm)

For each set of parameters described above, a joint integration may be applied, where the amount of change within the prediction product segment needs to be defined as:

dT = integral period time variation

dW = integral section weight change

dH = integral segment height change

dX = integral segment distance variation

The integration segments are given an initial condition reference "i", an ending condition reference "f", and then the following relationship exists for each integration segment:

T _f ＝T _i +dT W _f ＝W _i -dW H _f ＝H _i ±dH X _f ＝X _i -dX

s102, acquiring a vertical flight stage of the aircraft according to judgment logic of the vertical flight stage, and executing from step S103 if the aircraft is in the pre-flight and take-off stages; if the climbing stage is in, starting execution from step S104; if the vehicle is in the cruising phase, starting from step S105; if in the descending stage, starting execution from step S109; if in the advanced stage, the process starts at step S110.

According to the data required by the vertical track prediction and the sequence and transition relation of the vertical flight stages in the whole flight process, the vertical 4D flight profile of the whole flight process can be calculated section by section according to the processing logic of each vertical flight stage; based on the flight characteristics of each vertical flight stage and the proportion of each vertical flight stage in the whole flight process, comprehensive evaluation and analysis are carried out on the calculation accuracy and the calculation efficiency, and a method of selectively using a performance database model and a first sex principle model for different flight stages is used to form an optimal combined model.

The judgment logic of the vertical flight stage is mainly judged according to the conditions of the air-ground state of the airplane, the selected guiding mode on the flight panel, the distance between the current position and the destination airport, the relation between the current altitude and the cruising altitude and the like.

The vertical flight phase represents a certain period in flight and mainly comprises: the total of 8 flight phases before flight, take-off, climb, cruise, descent, approach, fly-away and after flight, the transition between each flight phase is processed according to the distance of the flight plan and the flight intention of the aircraft, for example the flight plan total distance is short and has a high cruise altitude, and the transition from the climb phase to the descent phase may occur without taking the minimum cruise flight time into account. The pre-flight stage refers to the stage before flight, the aircraft is positioned on the ground, the system power-on and the starting of the engine are completed, various avionics devices are turned on, and the aircraft is pushed out from the parking apron and slides to the runway entrance; in the take-off stage, the recovery of the flap and the landing gear is completed, and the speed is accelerated to reach a certain stable value; the climbing stage extends from the end of the take-off stage to the cruising height, namely a T/C point; the cruising phase extends from the end of the climbing phase to the beginning of the descending phase, namely a T/D point, and comprises cruising ladder climbing and ladder descending; a descent stage, wherein the aircraft leaves the designated cruising altitude, gradually decreases in altitude, and extends to a near stage start point; the approach stage extends from an initial flap deployment point to a landing point; the fly-away stage starts at a fly-away point or a position point when a flight unit starts fly-away, and ends at a height constraint defined in a fly-away program; the post-flight phase generally refers to the taxiing process of landing at the destination airport after the flight is completed. A typical aircraft 4D vertical flight profile is shown in fig. 3, giving an indication of the flight phase, as well as waypoint speed constraints, altitude constraints, airport speed limits, etc. that may be encountered in the vertical profile.

S103, processing the vertical track prediction in the take-off stage by adopting a performance database model.

The method regards the take-off phase as a whole, and does not divide the take-off phase twice any more, namely the take-off phase is regarded as an integral section, because the take-off phase has small speed and short time and the oil consumption ratio in the whole flight is relatively small. The vertical trajectory prediction for the take-off phase calculates the amount of change in time, fuel, distance and altitude for the take-off phase based on a simple performance database model. The complex first principle model is not used for calculation, because the compromise between the calculation precision and the calculation efficiency is considered through comprehensive analysis and multiple test comparison, and the vertical track prediction and optimization function is updated periodically, so that a certain precision loss in the initial stage of prediction is acceptable, the precision loss also disappears after leaving the take-off stage, and the influence is not accumulated in the subsequent flight stage. The process carries out interpolation inquiry from a performance database, predicts the acceleration height input by a human-computer interface or the height above the default runway (or airport) elevation from the starting position of take-off prediction, namely the height at which the climbing stage starts, so that the take-off stage carries out integral calculation once according to the integral step length of the height, the unconsumed parts of time, fuel oil and distance are added into the initial value of state parameters, the waypoints falling into the integral stage carry out interpolation inquiry from the performance database, and the vertical 4D track profile of each waypoint in the take-off stage is determined.

S104, processing the vertical track prediction of the climbing leg by adopting a first principle model.

A complete climbing process is typically made up of several legs, one leg also possibly spanning two or more flight phases. To meet the initial climb phase of airport speed limits, which is a height dependent speed limit, below which the speed cannot exceed a certain value, for example, below 10000ft the flight speed cannot exceed 250 knots; accelerating from the speed limited by the airport speed to a planned table speed corresponding to a climbing speed mode or a climbing accelerating section generated due to the speed constraint of the waypoint; the aircraft climbs at a constant planned speed until reaching a climbing equal speed section with a crossing height, wherein the crossing height is the height that the vacuum speed of the speed is equal to the vacuum speed corresponding to Mach number; at the height higher than the crossing height, the speed must be changed from the table speed to the Mach number, which is an equal Mach number climbing section climbing at a constant Mach number, until reaching the cruising height; it is also possible to include cruise flat flights generated due to altitude constraints of waypoints or altitude of airport speed limits.

Vertical trajectory prediction of climbing legs is typically based on climbing vertical profiles at specified climbing elevations and velocities, using a logical process as shown in fig. 2, each leg falling into the climbing phase is processed in turn. In the vertical track prediction of any leg in the climbing stage, the vertical integral section is processed, multiple integral sections may be involved in one leg, and when the leg is encountered in one integral section and is terminated, the leg is retracted to the termination position, so that the horizontal section and the vertical section are mutually coupled. And calculating the variation of time, distance, oil consumption and altitude in one integration section based on the complex first sex principle model, adopting an altitude integration step length or a time integration step length according to the variation of the aircraft climbing rate, and continuously carrying out the integration process until the aircraft is predicted to reach a climbing vertex (T/C point), namely reaching the cruising altitude. The process takes into account speed constraints, altitude constraints, time constraints and airport speed constraints of waypoints, while taking into account acceleration processes during climb. Descent behavior during climb should be prevented and waypoint altitude constraints, when encountered as part of a vertical flight plan, are prioritized over optimal climb vertical profiles.

FIG. 4 is a schematic illustration of a typical climbing vertical profile that takes into account waypoint speed constraints and altitude constraints during the climbing phase.

S105, processing the vertical track prediction of the cruising flight segment by adopting a first principle model.

A complete cruising process is generally made up of several segments: a cruise acceleration section for climbing speed to cruise speed; cruise segments of equal table speed or mach number; a step climbing section and a step descending section; further comprising a cruise deceleration section for decelerating from a cruise speed to a descent speed. The vertical trajectory prediction during cruise phase is typically based on an optimal speed vertical profile at a specified cruising altitude and provides one or more pre-planned cruise steps and a calculated optimal cruise step. The step climb and step descent may be pre-planned by the aircraft to step climb or step descent at a designated waypoint, or the flight management function may calculate an optimal step position and an optimal altitude to alter the optimal step for cruising altitude, wherein the optimal step position is determined based on the weight of the aircraft. The termination check and processing of the cruise leg should include a check to determine whether the calculated optimal step climb point is reached or whether the planned step climb point is reached.

Taking into account the step climb and step descent, and the acceleration and deceleration processes that may be present at the beginning and end of cruising, each leg that falls into the cruising phase is processed in turn using a logic process as shown in figure 2. When vertical track prediction is carried out on any section of the navigation section in the cruising stage, vertical integral section processing is carried out on the navigation section, the navigation section is retracted to the end position of the navigation section when the navigation section is ended in one integral section, and the horizontal section and the vertical section are mutually coupled. The cruising fuel flow in one integral section is calculated based on a complex first principle model, any one of three integral steps of weight, distance and time is adopted, and then the variation of time, distance and fuel consumption in one integral step is calculated, and the integral process is continued until the prediction reaches a descending peak (T/D point), namely, the prediction of entering the descending section is stopped. The step climbing and the step descending can be regarded as high constraint in the cruising process, and a vertical track prediction method similar to the climbing stage and the descending stage can be adopted, so that the track prediction and optimization in the cruising stage are considered in the step climbing and the step descending process.

FIG. 5 is a schematic illustration of a typical cruise vertical profile including a planned cruise step and a calculated optimal cruise step.

And S106, when the cruise flight process is performed, if the flight plan is found to be changed, the step 107 is performed, and if not, the step 109 is performed.

S107, judging whether the descending bottom point (B/D point) exists, and if not, entering step 110, and if so, entering step 108.

S108, constructing a descent path. The descent path is a sequence of paired distance and altitude to the destination airport with reference to the ground, called descent path, in order to provide a pre-planned descent profile for the descent phase and approach phase, so that the aircraft can perfectly land on the destination airport while flying along the descent profile. The vertical trajectory prediction and optimization function should refer to the descent path as the planned vertical profile of the descent phase, while the vertical guidance function provides vertical navigation during the descent phase with the reference path as the target path. The descent path may be generally divided into a slow path section and a geometric path section, and should be constructed by calculating a cruising altitude from a B/D point in a direction opposite to the flight based on a slow thrust or a near slow thrust and a speed plan for optimizing an operation, and determining a position point from the cruising altitude to the descent phase, i.e., a T/D point in advance. The slow path segment, also referred to as the performance path segment, within which no constraints and ATC intervention are imposed, may perform Continuous Descent Operations (CDOs) for fuel/time efficient descent operations. The geometric path section is mainly constructed based on altitude constraint, speed constraint, airport altitude limitation and flight path angle constraint, and is mainly characterized in that altitude and distance meet a certain angle relation, but the slow vehicle path section has no such remarkable characteristic. If there are no altitude constraints or airport speed limits during the descent phase, the entire descent path is constructed based on the slow path segments. The descent path constructed should be aeroplane-flyable and if this cannot be done, an appropriate indication should be provided to the flight crew. A schematic of a typical constructed descent path is shown in fig. 6.

S109, processing the vertical track prediction of the descending leg by adopting a first principle model.

The prediction of the vertical trajectory of the aircraft along the descent path requires consideration of anomalies of the deviation of the aircraft from the descent path, mainly because the aircraft may descend in advance or be delayed, i.e. the descent position at which the aircraft starts is not expected, mainly including both above and below the descent path, in order to simulate how the vertical guidance function recaptures and tracks the descent path. The flight of the descent phase is similar to the climbing phase, but in the opposite sense is also generally composed of several sub-phases: an equal Mach number descent segment for flying according to the Mach number of the descent schedule; an equal-table-speed descending section for flying according to the table speed of the descending plan; a descent acceleration segment generated by decelerating from a planned table speed corresponding to the descent speed mode to a speed limited by the airport speed or due to the waypoint speed constraint; a descending deceleration section; and continuing to descend to the constant-speed section at which the approach stage begins according to the speed limit of the airport; it is also possible to include cruise flat flights generated due to altitude constraints of waypoints or altitude of airport speed limits.

Vertical trajectory prediction for the descending leg uses a logical process as shown in fig. 2, which processes each leg in turn that falls into the descending leg. When vertical track prediction is carried out on any section of the descending section, vertical integral section processing is carried out on the section, the section is retracted to the section termination position when the section is terminated in one integral section, and the horizontal section and the vertical section are mutually coupled. The variation of time, distance, oil consumption and height in one integration section is calculated based on a complex first sex principle model, and the integration process is continued until the prediction reaches the starting point of the approaching stage by adopting the height integration step length. This process takes into account speed constraints, altitude constraints, time constraints and airport speed limits of waypoints, as well as deceleration processes during descent. Climbing during descent should be prevented and when waypoint altitude constraints are encountered, these constraints take precedence over the optimal descent profile.

Fig. 6 is not only a schematic illustration of the completed descent path, but also a substantially vertical descent flight profile of the aircraft while flying in accordance with the descent path.

The approach stage is small in speed and time, oil consumption in the whole flight is relatively small, but considering that the approach stage has more deceleration processes, the simple processing can directly influence the vertical track prediction information of a destination airport. The method considers a simple performance database model to calculate the variation of time, distance, oil consumption and height in one integral section, and does not use a complex first sexual principle model for calculation, because the compromise between calculation accuracy and calculation efficiency is considered through comprehensive analysis and multiple test comparison; on the other hand, the processing of the approach stage does not use a simplified processing method which regards the whole stage as an integral section like the take-off stage, the integral section is divided, the characteristics of relatively short distance, relatively short flight duration and the like of the approach stage are considered, the period of the vertical track prediction and optimization function is updated, and the precision loss caused by the method using the performance database model is basically within the precision requirement range along with the continuous advancing of the flight. The integration process is continued until the destination airport is predicted, and the predicted value at the end of integration is the predicted information of the destination airport.

S111, if the fly-away stage is activated, the vertical track prediction in the fly-away stage is processed by adopting a performance database model, otherwise, the step S113 is performed.

Since the fly-away phase requires activation of the aircraft set, no prediction is provided prior to activation of the fly-away phase, which is typically initiated at the fly-away point or at the location where the aircraft set initiates the fly-away and terminated at the altitude constraint defined in the fly-away procedure. The vertical track prediction processing in the fly-away stage is similar to that in the take-off stage, and the fly-away stage (i.e. an integral step length) is processed by adopting a method of a performance database model, and the details are not repeated.

S112, the vertical track prediction of the spare descent route is processed by adopting a performance database model.

The method comprises the steps of processing a spare landing flight path, considering two spare landing types of flying and direct flying, and determining a vertical flight phase to be contained in the spare landing flight plan according to the spare landing flight plan and the spare landing cruising altitude, wherein the whole spare landing flight plan adopts a performance database model to calculate the time, the distance, the fuel oil and the altitude variation of the spare landing flight path and the prediction information of a spare landing airport. The method for calculating the whole standby route by adopting the performance database model instead of the first sex principle mainly has the advantages that the selection of the standby airport is generally closer to the target airport, namely the standby flight planning distance is relatively shorter, the flight time of the standby route is relatively shorter, the compromise between the calculation precision and the calculation efficiency is considered, and the performance database model is sufficient to support the required vertical track prediction precision through comprehensive analysis and experimental comparison.

According to the optimization index of the vertical track, the method calculates recommended aircraft state parameters based on a first sex principle model or a performance database model while considering aircraft performance limit, waypoint constraint and civil airspace flight rules, and optimizes the vertical flight profile to meet a task target. And taking the optimized state parameter as the state parameter of the initial position of the aircraft to participate in the vertical track prediction process updated in the subsequent period, and optimizing the vertical flight profile of the whole process.

FIG. 2 is a low level logic flow diagram of the next level of control leg processing of the present invention, which is a general method of vertical trajectory prediction for three stages of climb, cruise, and descend, illustrating the method of dividing vertical trajectories for three stages of climb, cruise, and descend into regions of uniform nature and single integration intervals for processing. When the aircraft is in three flight phases of climbing, cruising and descending, short-time vertical trajectory prediction based on the current vertical mode is considered for correlation with the vertical guiding function and reference is provided for vertical guiding.

S201, acquiring data of a next navigation segment. The vertical trajectory prediction logic of the climbing, cruising and descending three flight phases is processed according to the flight plan flight phase, namely, a plurality of flight phases can exist in one flight phase, and one flight phase can also span two or more flight phases, so that the processing processes of the flight phases are mutually coupled in the horizontal direction and the vertical direction, and the horizontal section and the vertical section need to be associated together. The primary task of controlling the logic flow of leg processing is to retrieve data for the next leg to be processed from a buffer in the flight plan leg store.

S202, setting a termination condition. This process selects the termination conditions that apply to the leg acquired at S201. "terminate" is a generic term for two cases, defined as:

a) Ending of the same attribute region (i.e. integral type changing) or

b) The points where the predicted data needs to be saved (e.g.: waypoints, T/C points, T/D points, speed change points, optimal cruise ladder points, etc.).

For the setting of the termination condition, before the integration is started, both the horizontal termination and the vertical termination points should be defined for the mutual coupling in the horizontal direction and the vertical direction. Interpolation of one integral segment or termination point is completed, and one or both of the horizontal termination and vertical termination will be ordered by the next valid value. Horizontal termination is defined as the distance to the destination airport; vertical termination is typically defined by a vertical leg type, associated with the integral leg in the form of a height value. Vertical termination is possible across multiple horizontal terminations until the integrated value accumulated meets a vertical termination criterion; horizontal termination is also possible across multiple vertical terminations until the accumulated integral value reaches a horizontal termination criterion. As an example, when a waypoint with a high constraint arrives at the climb or descent leg integration process, the horizontal and vertical stops are ordered at the same time.

S203, selecting the integral type, the process evaluates the type of the unified property area to be integrated, and determines the required integral type. For the prediction and optimization of the vertical trajectory, as described above, the first division divides the flight according to the flight phase, and the take-off and take-off phases are not further divided as other phases. The approach phase performs division of the product segments, but is a relatively special division process. The next split is to split the climb, cruise and descent flight phases into vertical legs, each characterized by a single speed pattern. Each leg extends from the end of the previous leg to its designated target altitude, or in the case of a cruising leg, to a planned step climb point, or to an optimal climb point or T/D point. The next partition divides each vertical leg into regions of uniform nature. At least one variable in the aircraft equations of motion in these regions may be considered constant, which also approximates regions where the aircraft crew or automatic guidance system will use a distinct control method. The main significance of this division is that it allows a relatively simple integration algorithm to be used for each region. The method provides 10 types of integral section types for processing the areas with uniform properties, and the detailed description table of the integral section step length is shown.

The final flight division divides each region of uniform nature into individual integration intervals. For example, during the climb phase of a target speed zone, assuming a division into height intervals of 1000 foot height step, if the zone spans 5000 feet, the integration will process 5 consecutive intervals to accumulate the total of the zone, as shown in FIG. 7, which is such a non-height constrained climb process.

S204, integrating an integration step length. According to the selected integration type, the calculation method based on the first principle of nature takes the atmospheric wind temperature model into consideration, calculates the data change amounts of the incremental units in one integration step range, and adds them to the previously accumulated calculated values. Integrating an integration step length, taking the integration step length with different values basically leads to different calculation results, and the smaller the integration step length is, the higher the calculation accuracy is, but the calculation amount is also increased sharply, and in the method, the compromise between the calculation accuracy and the calculation efficiency needs to be considered, so that the selection of the integration step length is carefully selected after multiple experiments are performed. The choice of integration step again varies with the type of integration, as shown in table 1:

TABLE 1

S205, whether the termination condition is passed. This step is used to determine if the set termination condition of S202, i.e. the set termination value is passed over a horizontal distance or over a vertical height, has been exceeded after integration by one integration step. If termination is detected, the data at the termination is stored and processed in S206; if the set termination value is not passed over either the horizontal distance or the vertical height, it is possible to integrate again an integration step according to the same type of integration and to determine again whether the termination condition is passed.

S206, the processing is terminated and data is stored. Typically, when a horizontal termination or a vertical termination is detected, the integrated value will exceed an exact termination criterion. Thus, the process interpolates back to the exact termination point in the last integration interval. At this point, the required data (e.g., predicted altitude, weight, speed, time, etc.) is stored in the appropriate location. The same type of next termination may be set before continuing, as appropriate.

S207, judging whether the terminal is a terminal end of the navigation section or not, and judging whether the terminal is a horizontal termination point or not. The terminated data is processed and stored in the processing terminated and stored data 206, and this step is used to determine whether it is a horizontal termination, and if so, the last leg 209 that enters the flight phase where it is in again makes a subsequent logical determination.

S208, whether the unified attribute area is ended is judged to be vertical termination or not, and if the unified attribute area is not ended, the integration step length can be integrated again by using the integration type of the last time; if the unified attribute area is over, a new integration type needs to be selected again, and integration is carried out according to the new integration type.

S209, judging whether the flight phase is the last flight phase of the flight phase, if so, ending the processing of the flight phase in the flight phase, judging the flight phase to be entered by using the transition logic of the vertical flight phase, executing the flow shown in FIG. 2 again, and entering the new flight phase for processing the flight phase; if the flight segment is not the last flight segment in the flight phase, that is, the current flight phase has the flight segment which is not processed, the next unprocessed flight segment needs to be acquired, and the flight segments in the flight phase are processed in sequence until all the flight segments in the flight phase are processed.

It will be understood that equivalents and modifications will occur to those skilled in the art in light of the present invention and their spirit, and all such modifications and substitutions are intended to be included within the scope of the present invention as defined in the following claims.

Claims

1. The method for predicting and optimizing the vertical trajectory of the aircraft based on the combined model is characterized by comprising the following steps of:

s101, initializing state parameters of the current position of the aircraft;

s108, constructing a descent path;

s110, processing vertical track prediction in a near stage by adopting a performance database model;

2. The method for predicting and optimizing vertical trajectories of an aircraft based on a combined model as set forth in claim 1, wherein in S102, the determination logic of the vertical flight phase is determined based on the air-ground state of the aircraft, the guidance mode, the distance of the current location from the destination airport, and the relationship between the current altitude and the cruising altitude.

3. The method for predicting and optimizing vertical trajectories of aircraft based on combined model as claimed in claim 1, wherein in S103, take-off phase is regarded as an integral segment, integral calculation is performed once according to height integral step length, unconsumed parts of time, fuel and distance are added to initial values of state parameters, route points falling into the integral segment are interpolated from performance database, and vertical 4D trajectory profile of each route point in take-off phase is determined.

4. The method for predicting and optimizing vertical trajectory of aircraft based on combined model as claimed in claim 1, wherein in S104, a climb phase is composed of a plurality of legs, comprising: an initial climbing stage meeting airport speed limits; accelerating from the speed limited by the airport speed to a planned table speed corresponding to a climbing speed mode or a climbing accelerating section generated due to the speed constraint of the waypoint; the aircraft climbs at a constant planned speed until reaching a climbing equal speed section at a crossing height; at the height higher than the crossing height, climbing the equal Mach number climbing section with constant Mach number until reaching the cruising height; it is also possible to include cruise flat flights generated due to altitude constraints of waypoints or altitude of airport speed limits;

5. The method for predicting and optimizing vertical trajectories of an aircraft based on a combined model of claim 1, wherein in S105, a cruising phase is comprised of a plurality of legs, comprising: a cruise acceleration section for climbing speed to cruise speed; cruise segments of equal table speed or mach number; a step climbing section and a step descending section; a cruise deceleration section that decelerates from a cruise speed to a descent speed;

6. The method for predicting and optimizing vertical trajectories of aircraft based on a combined model as claimed in claim 1, wherein in S108, the descent path is divided into a slow path section and a geometric path section, the slow path section is constructed by calculating a cruising altitude from a descent bottom point in a direction opposite to a flight based on a slow thrust or a near slow thrust and a speed plan for optimizing an operation, and determining a position point from the cruising altitude to a descent stage in advance; the geometric path segment is constructed based on altitude constraints, speed constraints, airport altitude limits, and flight path angle constraints.

7. The method for predicting and optimizing vertical trajectory of aircraft based on combined model as claimed in claim 1, wherein in S109, the descending stage is composed of a plurality of legs, comprising: an equal Mach number descent segment for flying according to the Mach number of the descent schedule; an equal-table-speed descending section for flying according to the table speed of the descending plan; a descent acceleration segment generated by decelerating from a planned table speed corresponding to the descent speed mode to a speed limited by the airport speed or due to the waypoint speed constraint; a descending deceleration section; and continuing to descend to the constant-speed section at which the approach stage begins according to the speed limit of the airport; it is also possible to include cruise flat flights generated due to altitude constraints of waypoints or altitude of airport speed limits;

8. The method for predicting and optimizing vertical trajectories of aircraft based on combined model as set forth in claim 1, wherein in S110, the approach phase is divided twice according to the altitude interval, i.e. the approach phase is regarded as a plurality of product segments, and the waypoints falling into the product segments determine their vertical trajectory prediction values by interpolation.

9. The method for predicting and optimizing vertical trajectories of an aircraft based on a combined model as set forth in claim 1, wherein in S112, the vertical trajectories of the descent route are predicted taking into account two descent types, namely, fly-in and fly-through, and the vertical flight phases to be included in the descent flight plan are determined based on the descent flight plan and the descent cruising altitude, and the entire descent flight plan calculates the time, distance, fuel and altitude variation of the descent route and the prediction information of the descent airport using a performance database model.