• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    Method (200), support and system for receiving a representation, by a mathematical model, of operating characteristics for a combination of an aircraft and a motor; perform on the representation by a mathematical model a reduction of order of the model by projection; to eliminate, from the projected model, the components of rapid dynamics of mathematical model representation; to determine a reduced-order model, in the form of a differential algebraic equation in which algebraic equations replace the fast dynamics; establishing a flight path angle and throttle angle as a control to greatly reduce fuel consumption for the combination of modeled aircraft and engine; discretize motion equations for the combination of a modeled aircraft and engine and formulate optimization equations in the form of a nonlinear programming problem; and determining an optimal open-loop control that strongly limits fuel consumption for the combination of an aircraft and a modeled engine to climb to a prescribed altitude and own airspeed.
    公开号:FR3040785A1
    申请号:FR1658136
    申请日:2016-09-01
    公开日:2017-03-10
    发明作者:Reza Ghaemi；Eric Richard Westervelt；Mark Darnell
    申请人:General Electric Co；
    IPC主号:
    专利说明:

    Optimization of the flight path by non-linear programming
    The present invention relates to the optimization of the flight path of aircraft and, in particular, the creation of optimally controlled flight paths by nonlinear programming.
    A flight management system (SGS) is an on-board computer system that performs a number of tasks, including flight management of a flight plan. SGVs have been used for many years and the programming techniques so far used by SGVs are designed for the computing capabilities of older generations of computerized systems. For example, prior art VMSs still in use today usually make assumptions about many of the complex and varied flight path parameters, including, but not limited to, fixed values (i.e. constants) for aspects relating to the aircraft and their operating characteristics and a constant value for aircraft maneuvers such as, for example, a constant speed of the aircraft during a climb phase of the flight. These SGVs usually assume a constant speed (not a reality-imposed constraint) during a flight path climb phase and rely on look-up tables to determine the constant climb speed to report at an altitude and a given cruising speed.
    It is therefore desirable to propose a system and a process capable of generating a control of the trajectories according to the actual conditions for particular flights and not according to supposed constraints, including optimized flight paths. The invention will be better understood from the detailed study of some embodiments taken by way of nonlimiting examples and illustrated by the appended drawings in which: FIG. 1 illustrates in the form of a graph the phases of a flight path according to one or more embodiments shown or described herein; FIG. 2 is a flowchart illustrating a process according to one or more embodiments shown or described herein; FIG. 3 is a graphical representation illustrating an example of flight trajectory and a flight trajectory according to the prior art, according to one or more embodiments represented or described herein; and FIG. 4 is a schematic illustration of a device according to some embodiments of the present invention.
    The present invention relates to optimization of non-linear programming guidance. For the purposes of the present description, the term "linear programming" designates the process of solving an optimization problem defined by a system of equalities and inequalities, called globally constraints, on a set of unknown real variables, as well as an objective-function to maximize or minimize, some of the constraints or the objective-function being non-linear. This is the mathematical optimization subdomain that addresses nonlinear problems. As used herein, the term "guidance" defines the control reference that minimizes a cost function and is provided to a feedback control system. In some embodiments, the present invention provides a method that determines optimal feedback control. A flight path can then be predicted by applying the determined command to the motion equations given the assumed initial operating modes and ambient conditions. In certain aspects, the present invention particularly relates to a system and a process for optimizing a phase or part of a nonlinear programming flight path. In some aspects, non-linear programming techniques can be used to more accurately and efficiently define a flight path optimization problem and to generate an optimally controllable trajectory. In some aspects, non-linear programming can be used to solve a guidance optimization problem (eg, to greatly reduce fuel consumption) that is defined by a constraint system on a set of unknown real variables. Previous attempts and systems, including old VMS, usually assume many constant variables (eg the aircraft mass is assumed to be constant despite changes due to fuel combustion, an obligation that the the aircraft's own speed is constant during a flight path climb phase, etc.) and / or, otherwise, do not take other variables into account. The combined use of non-linear programming techniques and state-of-the-art computing means can provide a mechanism for addressing and generating a solution to the complex linear problem (s) of guidance optimization. In some aspects, the processes and systems described herein may eliminate or at least greatly reduce the reliance on assumptions and other (arbitrary) constraints that are unrealistic for determining optimal control. In addition, the proposed non-linear programming can cope with all types of constraints that the aircraft may have to satisfy, including altitude-speed, altitude-distance and speed-distance constraints. For the purposes of this description, the term "aircraft", "airplane" or "airplane" may include commercial aircraft covered by Title 14 of Part 25 of the Code of Federal Regulations (14 CFR part 25) containing rules of Airworthiness: Airplanes of category Transportation, drones and other air vehicles.
    Referring to Figure 1, a flight path 100 for an aircraft is illustrated in the form of a graph. The flight path generally comprises three phases or parts. In particular, in FIG. 1 is shown a flight trajectory 100 which comprises a climb trajectory 105, a cruise trajectory 110 and a descent trajectory 115. The graph of FIG. 1 illustrates the general relations between the altitude (axis vertical) and the range of an aircraft (horizontal axis) for a fixed-wing aircraft. In some embodiments, the processes and systems presented herein may be adapted to determine optimal control for the flight path rise phase 105, a goal of optimization is to minimize fuel consumption for as long as possible. the climb phase of the flight path while satisfying the desired distance, altitude and speed for the start of the cruise phase of the flight path and, in no way limiting, other types of constraints required for the flight path. In some embodiments, aspects of the present invention may be extended to include, at least in part, the cruise and / or descent phases of a flight path.
    Referring to Figure 2, there is presented a process 200 relating to the determination of an optimal command for an aircraft with a defined objective function. In some embodiments, the process 200 relates to determining a controlled path for the climb path of a particular aircraft. In certain embodiments, the problem of optimizing a climb path for an aircraft consists of eliminating, eliminating or at least greatly limiting according to the present invention the magnitude of the operational constraints taken into account to determine the optimal command. It should be noted that real operational constraints may exist and serve to determine the optimal flight path. For example, real-world operational constraints such as, for example, a maximum speed at specific low altitudes, a request from an official organization for the aircraft to fly to certain waypoints, and Other operational constraints may be fully taken into account in certain processes of the present invention including, but not limited to, the process proceeding as in Figure 2.
    In some embodiments, the problem of optimizing a flight path can be formulated as a non-linear programming optimization problem. In this way, all the real constraints of the problem can be taken into consideration by nonlinear programming. For example, constraints such as the trajectory of the flight path by a particular aircraft, the particular engine (s) used with the aircraft, the particular manufacturer of the airframe and the specific characteristics of the aircraft. this for the flight path, statutorily imposed flight restrictions, etc. can be taken into account according to some embodiments of the present invention. These and other constraints can be translated into nonlinear mathematical programming equations to determine the optimal solution taking into account the real constraints without the need to impose unnecessary, unrealistic or arbitrary constraints or assumptions.
    Overall, the problem of optimizing certain embodiments of the present invention can be formalized by obtaining a precise model of the aircraft concerned and its engine (s), by imposing constraints due to to the reality in the problem and by determining a nonlinear programming solution for a desired optimization function (eg the maximum limitation of fuel consumption for a flight path).
    Process 200 provides a process for generating optimal control according to some embodiments of the present invention. In the operation 205, a representation of operating characteristics for a combination of an aircraft and a motor is received in the form of a mathematical model. The representation of operating characteristics for a combination of an aircraft and a motor in the form of a mathematical model according to the present invention accurately unites the aircraft and engine model employed in a linear programming solver which provides an optimal flight path to save more fuel. The representation of operating characteristics for a combination of aircraft and engine by a mathematical model may include specific engine models for each particular aircraft, precise aerodynamic models for each particular aircraft, engine degradation models ( available, eg from engine manufacturers) for particular engines used with a particular aircraft, fuel combustion rates (eg as a function of altitude, speed, inclination of the throttle, etc.) for the specific aircraft, and other actual (ie, imposed by reality) additional, alternate or alternative constraints.
    In some embodiments, the representation of operating characteristics for the combination of an aircraft and a motor in the form of a mathematical model, used in the operation 205, may be derived or otherwise determined for an organism implementing at least some of the operations of the process 200. The mathematical model can be derived before the operation 205. In some embodiments, as part of the operation 205 or as a separate operation, the representation of Operating characteristics for the combination of aircraft and engine in the form of a mathematical model can be verified by a process matching the model to flight aid data. Operation 210 comprises performing a projection on the representation, by a mathematical model, of the operation 205. In certain aspects, the complete model is projected in a vertical plane so that the model represents only a movement longitudinal (ie the movement concerned by the current optimization of the flight path). In this way, the number of equations needed to accurately and comprehensively represent the flight path can be reduced.
    During the operation 215, the fast dynamics components of the mathematical model henceforth represented by the model of the operation 210 can be eliminated. At least some of the rapid dynamics components of the model can be eliminated in order to reduce the computational burden associated with the process 200. In some embodiments, for example, some changes in the weight of the aircraft, changes in Altitude and speed changes occur in minutes, compared with other changes (ie fast dynamics) that occur in seconds. By eliminating this fast dynamic, efficient control can be achieved efficiently while maintaining a high degree of accuracy. Operations 210 and 215 may constitute, at least partially, a pattern reduction process.
    Turning to operation 220, a reduced order model is determined. The reduced order model includes a differential algebraic equation or a system of differential algebraic equations where the algebraic equations replace the fast dynamics. Process 200 further includes operation 225 which includes establishing or selecting a flight path angle and throttle angle as a control to minimize fuel consumption for the combination of aircraft and engine modeled.
    In some embodiments, an altitude of the combination of the aircraft and engine modeled can be treated as an independent variable. Initially, in the mathematical model of the combination of the aircraft and the engine, which is represented in the form of differential algebraic equations, the derivative of states (variables) is a function of time. In some embodiments, the independent variable is not time, but altitude. That is, all differentiations in differential algebraic equations are relative to altitude. As a result, all other variables, including time, are formulated as altitude-dependent variables in the aircraft's mathematical model. This altitude processing may be possible because it is desirable for the aircraft to reach the end point of the climb (ie the beginning of the cruise phase of the flight path, reference point 120 in Figure 1) to a specific altitude.
    In some embodiments, aircraft performance and airspace boundaries may be defined as state and / or control constraints for the optimization problem to be solved by process 200. In operation 230, the process 200 includes the definition of a final cost of climb as a function of altitude and cruising speed. Cruise conditions are taken into account in the definition of the cost to account for cruising flight at the end of the climb phase. The cost of cruising is shown as the final cost: - (fuel burned at cruising per unit distance) * (total climb distance). With this term, climb optimization is performed for all trajectories negotiated during the climb phase and part of the cruise phase so that all trajectories arrive at the same distance, altitude and the same speed cruising somewhere near the end of the climb. Thus, in some embodiments, not only is a trajectory negotiated during the climb phase with a minimal fuel consumption defined, but also a trajectory comprising the course of a certain additional distance which therefore burns fuel during the cruising phase to arrive at the same distance as other trajectories is determined once the trajectory has arrived at the same distance. This type of trajectory will have consumed relatively more fuel than the trajectory comprising only the climb phase.
    Moving on to operation 235, the equations of motion for the combination of aircraft and engine modeled (ie the equation of motion of the complete flight path) can be discretized and formulated as a problem of non-linear programming aimed at greatly limiting the fuel costs of the flight path climb phase. The form of embodiment of the non-linear programming problem aimed at greatly limiting the fuel costs of the flight path rise phase is a specific distance from a more general problem of direct operating cost limitation. The problem of non-linear programming of the operation 235 can therefore be solved in order to determine an optimal open loop which strongly limits the fuel consumption for the combination of the aircraft and the engine modeled so as to climb up to an altitude and prescribed cruising speed, as illustrated by operation 240 of Figure 2. The prescribed cruising altitude and cruising speed may correspond to point 120 or around point 120 of Figure 1. In certain embodiments, the trajectory of flight can be determined from optimal motion equations of an open-loop control vehicle.
    In some embodiments of the present invention, the process 200 and other processes including at least some aspects thereof provide a number of improvements, enhancements, and features. Some of these improvements, enhancements, and features may include, but are not limited to, an ability to optimally cope with altitude-velocity, distance-velocity, distance-altitude constraints; to allow for optimum speed, flight path angle and / or thrust to minimize the Direct Operating Cost; to provide ride quality and operating constraints, including jerk and acceleration limits; to take into account the winds at altitude in the optimization; to take into account the actual performance of the engine as it deteriorates over time, for example on the basis of a custom engine model; to allow higher-order motion equations (compared to other methods), including mass as a state variable by excluding hypotheses from other processes that assume the mass is constant; and to allow the use of a cost index to define the cost of time and fuel in the cost functional, thereby allowing for a process of greatly limiting the direct operating cost.
    In some embodiments, the process 200 and at least one or more operations thereof may be extended to a process of optimizing the complete flight path. Thus, in some embodiments and in other aspects presented herein, the process 200 or portions thereof may be used to determine optimized flight paths for phases or portions of a flight path other than and / or in addition to the climb path, such as, for example, the cruising path, the descent path and combinations thereof.
    In some embodiments, systems and devices such as a flight management system (VMS) may be designed, enhanced, upgraded, supplemented, and executed differently to implement one or more of the processes and operations described herein for optimize flight guidance by non-linear programming. In particular embodiments, the process 240 of the process 200 may be implemented by the SGV and / or other systems. In some cases, a pilot or other person in charge of the aircraft may generate a flight path using one or more of the processes and operations presented here. A flight path plane thus generated can then be used to guide the maneuvers of the aircraft. In certain embodiments, the SGV and / or one or more other system (s) may use one or more of the processes and operations described herein to update a flight path plan for an aircraft in the event that Operations and processes change sufficiently (i.e., exceed a certain minimum threshold) after an initial or anterior flight path plan has been generated according to processes of the present invention. In some embodiments, the process 200 and other methods, as well as the systems and devices presented herein, may be employed in commercial aircraft (Part 25 of the CFR).
    Figure 3 is an illustration, in the form of a graph 300, showing a plot for a modeled aircraft climb path according to the present invention. In particular, there is shown a 305 anterior / old plot where the aircraft is limited to maintaining a constant speed during the entire climb phase of the flight path. However, the plot 310 corresponding to a flight path plane including aspects of the present invention where the aircraft is not limited or reduced to maintain a constant speed throughout the flight path rise phase, in the aim to minimize fuel consumption as much as possible. As shown, the conventional corrected clean airspeed (VC) for the flight path plane 310 shown here varies greatly as the aircraft climbs to the prescribed final altitude and speed, as indicated by point 325. It should be noted that the trajectories for the prior art plane as well as the plane according to the present invention both end at the same distance, the same altitude and the same speed. The lines 315 and 320 illustrate the result of a follow-up respectively for the plane according to the prior art and the plane according to the present invention.
    It will be appreciated that the applicants of the present invention have made improvements using the processes described herein. For example, by modeling a Boeing 737-800 equipped with CFM56 engines and using the processes described here, an optimal flight path was generated for prescribed operating scenarios. The flight path generated was negotiated using the combination of the aircraft and modeled engines, and fuel consumption was measured during the climb phase. The resulting fuel consumption was compared with the fuel consumed by the aircraft flying in a flight path according to the prior art constant speed optimization technique.
    The processes described herein including, but not limited to, the process 200, may be implemented by a system, application, or apparatus designed to perform process operations. In some embodiments, various hardware elements of an apparatus, device, or system execute program instructions to implement the process 200. In some embodiments. Hardwired circuits may be used in place of program instructions, or in combination therewith, for the implementation of processes according to some embodiments. Program instructions that may be executed by a system, device, or apparatus to implement the process 200 (and other processes or portions thereof described herein) may be stored on or otherwise in the form of non-transitory material supports. Therefore, the embodiments are not limited to any specific combination of hardware and software.
    Figure 4 is a block diagram of an assembly of a system or apparatus 400 according to some embodiments. The system 400 may, for example, be associated with any of the systems described herein including, for example, a VMS deployed in an aircraft deployed in an aircraft, a ground system and a portion of a service provided by the aircraft. intermediate of the "Cloud". The system 400 comprises a processor 405, such as one or more central unit (s) (CPU) available on the market or made specifically in the form of single-chip microprocessors or a multi-core processor. coupled to a communication device 420 adapted to communicate with another device or system via a communication network (not shown in Figure 4). In the case where the system 400 includes a device or system deployed in an aircraft, the communication device 420 may have a mechanism for interfacing the system with other onboard or remote applications, devices, systems, or services. The system 400 may also include a cache memory 410 such as random access memory modules. The system may further include an input device 415 (eg a touch screen, a mouse and / or a keypad for inputting content) and an output device 425 (eg a touch screen, a touch screen). computer display, a liquid crystal display).
    The processor 405 communicates with a storage device 430. The storage device 430 may include any appropriate information storage device, including combinations of magnetic storage devices (eg a hard disk drive), optical storage devices, semiconductor readers and / or semiconductor memory devices. In some embodiments, the storage device 430 may include a database system, including in some embodiments a database in memory, a relational database, and other systems.
    The storage device 430 may store code or program instructions capable of providing processor executable instructions for managing a flight path optimization generator according to methods presented herein. The processor 405 may execute the instructions of the program instructions 435 to thereby operate according to any of the embodiments described herein. The program instructions 435 can be stored in a compressed, uncompiled and / or encrypted format. The program instructions 435 may further include other program elements, such as an operating system, a database management system, and / or device drivers used by the processor 405 to interface with each other. with, for example, peripherals (not shown in Figure 4). The storage device 430 may also contain data 440 such as engine flight path data presented in some embodiments herein. Data 440 may be used by system 400, in some aspects, to implement one or more of the processes presented herein, including individual processes, individual operations of these processes, and combinations of different processes and process operations. .
    All the systems and processes mentioned here can be implemented in a program code stored on one or more hardware (s), its transient (s), exploitable (s) by computer. Such media may include, for example, a floppy disk, a CD-ROM, a DVD-ROM, a flash memory drive, a magnetic tape, and solid-state storage units in RAM and in ROM ( ROM). Therefore, the embodiments are not limited to any specific combination of hardware and software.
    It is intended by the present invention that additional parameters may be considered to generate an optimized flight path in addition to those specifically presented here by way of example. In addition, it is expected that the aspects and embodiments mentioned involving the use of linear programming can sufficiently manage and process these other parameters related to the flight.
    List of landmarks
    Number Designation 100 graph of a flight path 105 flight path 110 cruising path 115 glide path 120 waypoint 200 flowchart 205 process operation 210 process operation 215 process operation 220 process operation 225 process operation 230 operation of the process 235 operation of the process 240 operation of the process 300 climb trajectory graph 305 flight plan trace according to the prior art 310 flight plan trace according to the present invention 315 trace result for the track 305 320 track result for the plot 310 400 system 405 processor 410 cache 415 capture devices 420 communication device 425 output device 430 storage medium 435 linear programming engine 440 flight path data
    权利要求:
    Claims (6)
    [1" id="c-fr-0001]
    A system comprising: a computing device (400) comprising: a memory (430) storing program instructions (435) executable by a processor; and a processor (405) for executing the executable program instructions (435) to cause the computing device (400) to: receive a mathematical model representation of operating characteristics for a combination of a aircraft and engine; perform by projection, on the representation by a mathematical model, a reduction of order of the model; to eliminate, from the projected model, the components of rapid dynamics of mathematical model representation; to determine a model of reduced order, in the form of a differential algebraic equation in which algebraic equations replace the fast dynamics; establishing a flight path angle and throttle angle as a control to greatly reduce fuel consumption for the combination of modeled aircraft and engine; Define a final climb cost based on cruising altitude and own speed; discretize motion equations for the combination of a modeled aircraft and engine and formulate optimization equations in the form of a nonlinear programming problem; and determining an optimal open-loop control that greatly limits fuel consumption for the engine and engine combination modeled to climb to a prescribed altitude and speed.
    [2" id="c-fr-0002]
    2. System according to claim 1, further comprising a verification of the representation, by a mathematical model, of the operating characteristics for the combination of an aircraft and a motor.
    [3" id="c-fr-0003]
    The system of claim 1, wherein the fast dynamic components of the representation by the mathematical model are eliminated by setting to equilibrium values a pitching moment of the vertical forces for the combination of an aircraft and an aircraft. engine modeled.
    [4" id="c-fr-0004]
    The system of claim 1, further comprising determining a flight path based on the determined optimum open loop control and motion equations for the modeled aircraft and engine.
    [5" id="c-fr-0005]
    The system of claim 1, wherein a climb rate and / or thrust for the combination of aircraft and engine modeled to climb to a prescribed altitude and speed is variable.
    [6" id="c-fr-0006]
    The system of claim 1, wherein the representation, by a mathematical model, of the operating characteristics for the combination of an aircraft and an engine comprises at least one of the engine degradation characteristics, the combustion of fuel based on flight variables, a flight dynamics model and combinations thereof.
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    优先权:
    申请号 | 申请日 | 专利标题
    US14/844.892|2015-09-03|
    US14/844,892|US9564056B1|2015-09-03|2015-09-03|Flight path optimization using nonlinear programming|
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