CN112506226B - Long-endurance unmanned aerial vehicle flight path planning method based on temperature constraint conditions - Google Patents
Long-endurance unmanned aerial vehicle flight path planning method based on temperature constraint conditions Download PDFInfo
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Abstract
The invention belongs to the technical field of unmanned aerial vehicle route planning, and provides a long-endurance unmanned aerial vehicle route planning method based on temperature constraint conditions. Dividing the task phase of the long-endurance unmanned aerial vehicle into a task preparation phase andin the task implementation stage, a descending-flat flying-ascending temperature control air route is designed in the task preparation stage, and the temperature of the unmanned aerial vehicle load is restrained in the task preparation stage; setting the load temperature of a navigation section descending section navigation point to be T1The load temperature of the flight point of the descending section to the horizontal flight section is T2The load temperature of a flight point of a horizontal flight section to an ascending section is T3The load temperature of the flight point of the ascending section to task implementation section is T4Establishing a temperature control equation set and boundary conditions, and calculating and obtaining T1、T2、T3、T4And 4, obtaining the positions of the key navigation points and the velocity vector information of the unmanned aerial vehicle, and finally obtaining the flight route in the task preparation stage. The invention realizes the temperature restraint of the load entering the target area and solves the problem that the load entering the target area cannot normally work due to the temperature.
Description
Technical Field
The invention belongs to the technical field of unmanned aerial vehicle route planning, and particularly relates to a long-endurance unmanned aerial vehicle route planning method based on temperature constraint conditions.
Background
With the development of long-endurance unmanned aerial vehicle platform technology and load technologies such as optics and microwaves, the aerial-to-ground observation system is widely applied. The planning of the flight route of the long-endurance unmanned aerial vehicle is the basis for effectively carrying out ground observation flight, the good route planning method can comprehensively consider the constraint conditions of the unmanned aerial vehicle, the load and the environment, the optimal route of task flight is searched, the task flight efficiency of the long-endurance unmanned aerial vehicle is improved, and the method has important scientific research significance and engineering application value.
At present, the flight route planning mainly adopts two modes of manual design and automatic planning. The manually designed flight path usually manually calculates the waypoints meeting the requirements of the mission and the airspace according to the preset flight mission, and then connects the waypoints by using a smooth curve according to the characteristics of the airplane to obtain the final mission flight path. The method is flexible, but low in efficiency and free of repeatability, waypoints need to be recalculated to form routes before the flight mission is executed each time, and the method gradually cannot meet the requirements of route planning along with the increase of the complexity of the flight mission. The automatic planning comprehensively considers multiple factors such as a target area, task time, energy consumption, environmental limitation and the like, and an optimal or required air route is searched for so as to complete the established task. It can be mathematically abstracted as solving the optimal control problem of functional extrema under differential equations, equalities and inequality constraints (Conway B. space project optimization [ M ]: Cambridge University Press, 2010). The automatic planning method based on the intelligent optimization algorithm is fast in development and achieves better effects, such as obtaining a low-altitude flight route with optimal comprehensive cost by combining a genetic algorithm and a Dubins curve, obtaining a shortest route under the constraint of a flight airspace boundary by carrying out global optimization on the route by using a route tree dynamic search method, and the like.
However, in the above flight path planning method, whether manual design or automatic planning, most of the constraints such as the performance of the unmanned aerial vehicle, the airspace limit, the target area, the cut-in direction and the like are only considered, and the operating temperature of the load is rarely used as the constraint and is taken into consideration in the flight path planning of the unmanned aerial vehicle. In the current earth observation load, some parts have temperature sensitivity, such as a dual-frequency laser radar and the like, and the load can be started to work within a certain temperature range. If the constraint condition of the load temperature is not considered in the flight route planning, the load is likely to enter a target area along a preset direction, but the normal starting operation cannot be performed due to the fact that the working temperature is not reached. At this moment, can only make unmanned aerial vehicle hover, wait for load temperature adjustment, get into the target area again, this undoubtedly greatly reduced the efficiency that unmanned aerial vehicle task was flown during long voyage, and promoted the risk that the task was flown. Therefore, there is a need to develop a method for planning flight routes of long-endurance unmanned aerial vehicles based on temperature constraints.
Disclosure of Invention
The invention aims to solve the technical problem that the unmanned aerial vehicle cannot be started up normally due to the fact that the load cannot reach the working temperature after entering a target area due to the fact that no load temperature constraint condition exists in the flight path planning of the unmanned aerial vehicle during long-term flight.
In order to achieve the purpose, the invention provides a temperature constraint-based flight path planning method for a long-endurance unmanned aerial vehicle, which comprises the following steps of:
step 2, setting the load temperature of a navigation point of a descending section of the cruise section to be T1The load temperature of the flight point of the descending section to the horizontal flight section is T2The load temperature of a flight point of a horizontal flight section to an ascending section is T3The load temperature of the flight point of the ascending section to task implementation section is T4；
Step 3, establishing a temperature control equation set in a task preparation stage as follows:
Φ＝AH(Te-T) (1)
Φ(dt)＝Cm(dT) (2)
Te＝Tsea level-(6×h) (4)
Wherein phi is heat transfer power; A. h, C, m are load characteristic parameters respectively representing convection heat transfer area, convection heat transfer coefficient, heat capacity and mass, and the series of parameters are measured or corrected to obtain experience fitting values; h is the flight altitude (in Km), s is the horizontal flight distance (in Km); t is the load temperature, TeAmbient temperature, both of which are related to height h; vDescendFor the velocity component, V, of the descending section unmanned aerial vehicle in the vertical directionRise upFor the velocity component, V, of the unmanned aerial vehicle in the vertical direction at the ascent stagePing FeiThe speed of the unmanned plane in the horizontal flight section;
(1) the Newton cooling formula is used for representing the heat transfer power generated by the temperature difference between the environment and the load in the flight process;
(2) the temperature rise formula is a differential form of a temperature rise formula, and the temperature change condition of the load is represented under the condition of heat transfer power phi;
(3) is a relation of time and height/distance, wherein the flight path is divided into a descending section, a level flight section and an ascending section, and the speed of each section is assumed to be stable;
(4) is a relation of ambient temperature and altitude, TSea levelRepresents the temperature at sea level, as a known parameter;
the above equation sets are combined to obtain first-order heterogeneous linear differential equations of the ascending section and the descending section respectively, and the equations have general solutions as shown in (5)
K＝AH/Cm
Where K is an empirical parameter consisting of 4 load characteristic parameters, J is a parameter of general solution, hLowest level ofThe flight altitude of the plane flight section is determined by the performance and specific tasks of the unmanned aerial vehicle and is known;
according to the requirement of the unmanned aerial vehicle on the ground observation task in long voyage, the boundary conditions are as follows:
T1＝Tcruising altitude (6)
T4＝TTarget height (7)
h1＝hCruise control system (8)
h2＝h3＝hLowest level of (9)
h4＝hTarget (10)
Wherein, TCruising altitudeFor the ambient temperature, T, of the unmanned aerial vehicle in the cruising phaseTarget heightFor the ambient temperature of the drone in the target area, hCruise control systemAltitude, h, of the cruising flight of the unmanned aerial vehicleLowest level ofFlight altitude h of flat flight section for unmanned aerial vehicleTargetBeing unmanned aerial vehiclesA mission flight altitude;
step 4, obtaining experience parameter K
Designing a short-distance flight route with a track similar to that of a task preparation stage, carrying out flight correction of the unmanned aerial vehicle, and recording measured values of load temperature and flight altitude in the whole flight process by using a temperature sensor additionally arranged on the load of the unmanned aerial vehicle;
fitting data by using a formula (5) to obtain an empirical parameter K in a general solution;
step 5, calculating the load temperature T of the flight point of the descending section to the horizontal flight section2
Calculating to obtain a load temperature function T of the descending section by using a formula (5), an empirical parameter K and boundary conditions (6), (8) and (9)Descending section(h) Further obtaining the load temperature T of the flight point of the descending section to the level flight section2
Step 6, calculating the load temperature T of the flight point of the horizontal flight section to the ascending section3
Calculating to obtain a load temperature function T of the rising section by using a formula (5), an empirical parameter K and boundary conditions (7), (9) and (10)Rising section(h) Further obtaining the load temperature T of the flight point of the flat flight section to the rising section3；
Step 7, calculating a load temperature function T of the level flight sectionPing Fei(S) and voyage S
For convenience of calculation, at the boundary between the descent segment and the flat flight segment, let s be 0, and use equation (5) and empirical parameter K, T2And T3And calculating to obtain a load temperature function T of the level flight sectionPing Fei(S), further obtaining a horizontal flight segment voyage S, which is as follows:
Jplane flight segment＝T2-TMinimum height
Step 8, obtaining key waypoints of the route
According to the flight course S of the flat flight section obtained in the step 7, the speed vectors of the descending section and the ascending section of the unmanned aerial vehicle are determined by the performance of the unmanned aerial vehicle, and the flight course of the ascending section and the descending section can be obtained as known speed vectors; gradually carrying out reverse thrust by the target waypoint, namely determining a boundary point of the ascending section and the task implementing section, a boundary point of the level flight section and the ascending section, a boundary point of the descending section and the level flight section and a boundary point of the cruise section and the descending section; thus obtaining the positions of 4 key navigation points and unmanned aerial vehicle speed vector information;
step 9, obtaining the flight route of the task preparation stage
And (4) connecting the 4 key navigation point positions and unmanned aerial vehicle speed vector information obtained in the step (8) with a straight line by using two sections of circular arcs, namely obtaining the flight path of the whole task preparation stage.
Further, the process of connecting the two arcs with the straight line to obtain the flight path in the whole task preparation stage is as follows, P1～P4Respectively 4 key waypoints; o is1～O4Circles tangent to the velocity vector of the unmanned aerial vehicle at the key navigation points are respectively provided, the radius of the circle is equal to the radius of a descending or climbing arc of the unmanned aerial vehicle, and the parameter is related to the performance of the unmanned aerial vehicle and is known; v1Cruising speed for the unmanned aerial vehicle; v2For the descending speed of the unmanned aerial vehicle, the vertical component of the unmanned aerial vehicle in the vertical direction is VDescend；V3For the flying speed of unmanned aerial vehicle, i.e. VPing Fei；V4For the ascending speed of the unmanned aerial vehicle, the vertical component of the unmanned aerial vehicle in the vertical direction is VRise up；V5The flight speed of the unmanned aerial vehicle is determined by the load requirement.
Furthermore, in an actual task, the empirical parameter K takes the same value in a descending section, a level flight section and an ascending section, so that the calculation is simplified and the test efficiency is improved.
Compared with the prior art, the invention has the following effective benefits:
1. the method includes the steps that temperature constraint conditions are brought into unmanned aerial vehicle flight route planning during long-term flight for the first time, temperature control of loads and unmanned aerial vehicle flight route planning are considered comprehensively, a task stage in the flight process is divided into a task preparation stage and a task implementation stage, temperature control is conducted in the task preparation stage, the loads are enabled to be smoothly transited to a target area after reaching a working temperature range, and therefore the loads can be enabled to work in a normal working state in the task implementation stage to complete a preset task;
2. the invention aims at the problem that the unmanned aerial vehicle carries a temperature sensitive load to carry out single-task flight during long-endurance, a load temperature control equation set and boundary conditions are established, a specific implementation method of route planning based on temperature constraint conditions is developed, the temperature sensitive load can simultaneously meet the position, speed direction and temperature conditions of entering a target area, the risk that the unmanned aerial vehicle cannot start due to temperature limitation when the load enters the task area is avoided, and the efficiency of the task flight of the unmanned aerial vehicle during long endurance is improved.
Drawings
FIG. 1 is a schematic diagram of a general process of single-mission flight of a long-endurance unmanned aerial vehicle;
FIG. 2 is a schematic diagram of a single-mission flight process of a long-endurance unmanned aerial vehicle designed by the present invention;
FIG. 3 is a schematic diagram of the process of connecting key waypoints into routes according to the present invention.
Detailed Description
The invention will be explained and explained in detail with reference to the drawings.
As shown in fig. 1, for a general single-mission flight of a long-endurance unmanned aerial vehicle, the whole flight process can be roughly divided into a take-off and landing stage, a cruise stage and a mission stage, such a flight path stage planning can only ensure that a load reaches a proper observation position in a target area, and does not consider the working temperature condition of the load, which may cause that a temperature-sensitive load is already at the observation position, but is limited by the insufficient temperature requirement, and cannot be started normally. The design idea of the invention is to incorporate temperature constraints into the planning of the flight route of the unmanned aerial vehicle, and as shown in fig. 2, the task phase is divided into a task preparation phase and a task implementation phase, wherein the task preparation phase controls the temperature to enable the load to reach the working temperature range and smoothly transit into the target area, thereby ensuring that the load can carry out operation in a normal working state in the task implementation phase to complete the predetermined task.
When the unmanned aerial vehicle carries a load to carry out long-distance observation during long-distance flight, the unmanned aerial vehicle carries out high-altitude flight during the cruising stage, and the environment temperature is relatively low at the moment; in the task implementation stage, some loads are generally close to an observation target in order to obtain higher measurement resolution, for example, a dual-frequency laser radar can work at a height of 1km of a field, and the ambient temperature is relatively high. From the cruise stage to the task stage, the load temperature rises along with the continuous descending of the height of the unmanned aerial vehicle, at the moment, how to determine the boundary point of the cruise stage and the task stage, how to plan the air route in the task preparation stage, how to ensure the smooth transition of the unmanned aerial vehicle from the task preparation stage to the task implementation stage is the key point for solving the technical problems.
In the cruising stage, the flight altitude of the unmanned aerial vehicle is generally unchanged, the ambient temperature can be considered to be unchanged, and the T is setCruising altitude(ii) a The load temperature in thermal equilibrium is approximately equal to the ambient temperature, i.e. T1＝TCruising altitude(ii) a During the flight process of executing the earth observation task, the unmanned aerial vehicle is generally at the same altitude in the target area, and the ambient temperature is regarded as being constant and is set as TTarget height(ii) a Load temperature T in the process4＝TTarget heightIf the load temperature at that time is within the allowable operating temperature range, i.e. TLower limit of<T4<TUpper limit ofAt the moment, the temperature control module is not additionally arranged, and the temperature control requirement can be met by completely utilizing route planning.
In the continuous descending process of the unmanned aerial vehicle, the load temperature rises, but the temperature change is limited by the heat transfer power, and a certain delay is generated. Set up in task preparation stageFor "descending-flat flying-ascending" temperature control flight path, as shown in FIG. 2, the unmanned plane is at a stable speed VDescend(vertical component of velocity vector) is lowered until the lowest altitude for safe sailing at a steady velocity VPing FeiFlat flight, when the ambient temperature is highest (denoted as T)Minimum height) The load can be heated as soon as possible and after a period of time, the load is heated at a stable speed VRise up(vertical direction component of velocity vector) rises, smoothing into the target area. The process temperature control equation set is as follows:
Φ＝AH(Te-T) (1)
Φ(dt)＝Cm(dT) (2)
Te＝Tsea level-(6×h) (4)
Wherein phi is heat transfer power; A. h, C, m are load characteristic parameters respectively representing convection heat transfer area, convection heat transfer coefficient, heat capacity and mass, and the series of parameters are measured or corrected to obtain experience fitting values; h is the flight altitude (in Km), s is the horizontal flight distance (in Km); t is the load temperature, TeAmbient temperature, both of which are related to height h;
(1) the Newton cooling formula is used for representing the heat transfer power generated by the temperature difference between the environment and the load in the flight process;
(2) the temperature rise formula is a differential form of a temperature rise formula, and the temperature change condition of the load is represented under the condition of heat transfer power phi;
(3) is a relation of time and height/distance, wherein the flight path is divided into a descending section, a level flight section and an ascending section, and the speed of each section is assumed to be stable;
(4) is a relation of ambient temperature and altitude, TSea levelRepresents the temperature at sea level, as a known parameter;
the above equation sets are combined to obtain first-order heterogeneous linear differential equations of the ascending section and the descending section respectively, and the equations have general solutions as shown in (5)
K＝AH/Cm
Where K is an empirical parameter consisting of 4 load characteristic parameters, J is a parameter of general solution, hLowest level ofThe flight altitude of the plane flight section is determined by the performance and specific tasks of the unmanned aerial vehicle and is known;
according to the requirement of the unmanned aerial vehicle on the ground observation task in long voyage, the boundary conditions are as follows:
T1＝Tcruising altitude (6)
T4＝TTarget height (7)
h1＝hCruise control system (8)
h2＝h3＝hLowest level of (9)
h4＝hTarget (10)
Wherein h isCruise control systemAltitude, h, of the cruising flight of the unmanned aerial vehicleLowest level ofFlight altitude h of flat flight section for unmanned aerial vehicleTargetFlying the altitude for the mission of the drone;
by introducing boundary conditions, a piecewise function relation of load temperature and height in the whole process can be obtained, so that waypoints meeting temperature constraint conditions are determined, as shown in fig. 3, the climbing or descending process of the unmanned aerial vehicle is decomposed into a combination of circular arcs and straight lines, all waypoints are connected, and the conditions of position and speed direction are guaranteed to be met simultaneously.
By the aid of the method, the unmanned aerial vehicle flight path planning method under temperature constraint is designed, a load temperature control differential equation and boundary conditions are established, temperature constraint of the load entering a target area is achieved, and the problem that the load cannot work normally due to temperature caused by entering the target area is solved.
The specific embodiment of the invention is as follows:
step 2, setting the load temperature of a navigation point of a descending section of the cruise section to be T1The load temperature of the flight point of the descending section to the horizontal flight section is T2The load temperature of a flight point of a horizontal flight section to an ascending section is T3The load temperature of the flight point of the ascending section to task implementation section is T4；
Step 3, establishing a temperature control equation set in a task preparation stage as follows:
Φ＝AH(Te-T) (1)
Φ(dt)＝Cm(dT) (2)
Te＝Tsea level-(6×h) (4)
Wherein phi is heat transfer power; A. h, C, m are load characteristic parameters respectively representing convection heat transfer area, convection heat transfer coefficient, heat capacity and mass, and the series of parameters are measured or corrected to obtain experience fitting values; h is the flight altitude (in Km), s is the horizontal flight distance (in Km); t is the load temperature, TeAmbient temperature, both of which are related to height h; vDescendFor the velocity component, V, of the descending section unmanned aerial vehicle in the vertical directionRise upFor the velocity component, V, of the unmanned aerial vehicle in the vertical direction at the ascent stagePing FeiThe speed of the unmanned plane in the horizontal flight section;
(1) the Newton cooling formula is used for representing the heat transfer power generated by the temperature difference between the environment and the load in the flight process;
(2) the temperature rise formula is a differential form of a temperature rise formula, and the temperature change condition of the load is represented under the condition of heat transfer power phi;
(3) is a relation of time and height/distance, wherein the flight path is divided into a descending section, a level flight section and an ascending section, and the speed of each section is assumed to be stable;
(4) is a relation of ambient temperature and altitude, TSea levelRepresents the temperature at sea level, as a known parameter;
the above equation sets are combined to obtain first-order heterogeneous linear differential equations of the ascending section and the descending section respectively, and the equations have general solutions as shown in (5)
K＝AH/Cm
Where K is an empirical parameter consisting of 4 load characteristic parameters, J is a parameter of general solution, hLowest level ofThe flight altitude of the plane flight section is determined by the performance and specific tasks of the unmanned aerial vehicle and is known;
according to the requirement of the unmanned aerial vehicle on the ground observation task in long voyage, the boundary conditions are as follows:
T1＝Tcruising altitude (6)
T4＝TTarget height (7)
h1＝hCruise control system (8)
h2＝h3＝hLowest level of (9)
h4＝hTarget (10)
Wherein, TCruising altitudeFor the ambient temperature, T, of the unmanned aerial vehicle in the cruising phaseTarget heightFor the ambient temperature of the drone in the target area, hCruise control systemAltitude, h, of the cruising flight of the unmanned aerial vehicleLowest level ofFlight altitude h of flat flight section for unmanned aerial vehicleTargetFlying the altitude for the mission of the drone;
step 4, obtaining experience parameter K
Designing a short-distance flight route with a track similar to that of a task preparation stage, carrying out flight correction of the unmanned aerial vehicle, and recording measured values of load temperature and flight altitude in the whole flight process by using a temperature sensor additionally arranged on the load of the unmanned aerial vehicle;
fitting data by using a formula (5) to obtain an empirical parameter K in a general solution;
step 5, calculating the load temperature T of the flight point of the descending section to the horizontal flight section2
Calculating to obtain a load temperature function T of the descending section by using a formula (5), an empirical parameter K and boundary conditions (6), (8) and (9)Descending section(h) Further obtaining the load temperature T of the flight point of the descending section to the level flight section2
Step 6, calculating the load temperature T of the flight point of the horizontal flight section to the ascending section3
Calculating to obtain a load temperature function T of the rising section by using a formula (5), an empirical parameter K and boundary conditions (7), (9) and (10)Rising section(h) Further obtaining the load temperature T of the flight point of the flat flight section to the rising section3；
Step 7, calculating a load temperature function T of the level flight sectionPing Fei(S) and voyage S
For convenience of calculation, at the junction of the descending segment and the flat flight segment, let s be 0, and use the formula(5) Empirical parameter K, T2And T3And calculating to obtain a load temperature function T of the level flight sectionPing Fei(S), further obtaining a horizontal flight segment voyage S, which is as follows:
Jplane flight segment＝T2-TMinimum height
Step 8, obtaining key waypoints of the route
According to the flight course S of the flat flight section obtained in the step 7, the speed vectors of the descending section and the ascending section of the unmanned aerial vehicle are determined by the performance of the unmanned aerial vehicle, and the flight course of the ascending section and the descending section can be obtained as known speed vectors; gradually carrying out reverse thrust by the target waypoint, namely determining a boundary point of the ascending section and the task implementing section, a boundary point of the level flight section and the ascending section, a boundary point of the descending section and the level flight section and a boundary point of the cruise section and the descending section; thus obtaining the positions of 4 key navigation points and unmanned aerial vehicle speed vector information;
step 9, obtaining the flight route of the task preparation stage
And (3) connecting the 4 key waypoint positions and unmanned aerial vehicle speed vector information obtained in the step (8) by using two arcs and a straight line to obtain a flight path in the whole task preparation stage, as shown in figure 3. Wherein, P1～P4Respectively 4 key waypoints; o is1～O4Circles tangent to the velocity vector of the unmanned aerial vehicle at the key navigation points are respectively provided, the radius of the circle is equal to the radius of a descending or climbing arc of the unmanned aerial vehicle, and the parameter is related to the performance of the unmanned aerial vehicle and is known; v1Cruising speed for the unmanned aerial vehicle; v2For the descending speed of the unmanned aerial vehicle, the vertical component of the unmanned aerial vehicle in the vertical direction is VDescend；V3For unmanned plane to fly at a speed, and VPing Fei；V4For the ascending speed of the unmanned aerial vehicle, the vertical component of the unmanned aerial vehicle in the vertical direction is VRise up；V5The flight speed of the unmanned aerial vehicle is determined by the load requirement.
In conclusion, the method realizes the flight route planning of the long-endurance unmanned aerial vehicle based on the temperature constraint, enables the temperature-sensitive load to simultaneously meet the position, the speed direction and the temperature condition of entering a target area, avoids the risk that the unmanned aerial vehicle cannot be started due to temperature limitation when the load enters a task area, and improves the task flight efficiency of the unmanned aerial vehicle.
Claims (3)
1. A method for planning a flight route of an unmanned aerial vehicle during long endurance based on temperature constraint conditions is characterized by comprising the following steps:
step 1, dividing a task stage of an unmanned aerial vehicle into a task preparation stage and a task implementation stage, dividing an unmanned aerial vehicle route in the task preparation stage into a descending section, a level flight section and an ascending section, designing a descending-level flight-ascending temperature control route, and carrying out temperature constraint on the load of the unmanned aerial vehicle in the task preparation stage;
step 2, setting the load temperature of a navigation point of a descending section of the cruise section to be T1The load temperature of the flight point of the descending section to the horizontal flight section is T2The load temperature of a flight point of a horizontal flight section to an ascending section is T3The load temperature of the flight point of the ascending section to task implementation section is T4；
Step 3, establishing a temperature control equation set in a task preparation stage as follows:
Φ＝AH(Te-T) (1)
Φ(dt)＝Cm(dT) (2)
Te＝Tsea level-(6×h) (4)
Wherein phi is heat transfer power; A. h, C, m are load characteristic parameters respectively representing convective heat transfer area, convective heat transfer coefficient, heat capacity and mass, and are measured or corrected to obtain empirical simulationThe sum value; h is the flight altitude, the unit Km, and s is the horizontal flight distance, the unit Km; t is the load temperature, TeAmbient temperature, both of which are related to height h; vDescendFor the velocity component, V, of the descending section unmanned aerial vehicle in the vertical directionRise upFor the velocity component, V, of the unmanned aerial vehicle in the vertical direction at the ascent stagePing FeiThe speed of the unmanned plane in the horizontal flight section;
(1) the Newton cooling formula is used for representing the heat transfer power generated by the temperature difference between the environment and the load in the flight process;
(2) the temperature rise formula is a differential form of a temperature rise formula, and the temperature change condition of the load is represented under the condition of heat transfer power phi;
(3) is a relation of time and height/distance, wherein the flight path is divided into a descending section, a level flight section and an ascending section, and the speed of each section is assumed to be stable;
(4) is a relation of ambient temperature and altitude, TSea levelRepresents the temperature at sea level, as a known parameter;
the above equation sets are combined to obtain first-order heterogeneous linear differential equations of the ascending section and the descending section respectively, and the equations have general solutions as shown in (5)
Where K is an empirical parameter consisting of 4 load characteristic parameters, J is a parameter of general solution, hLowest level ofThe flight altitude of the plane flight section is determined by the performance and specific tasks of the unmanned aerial vehicle and is known;
according to the requirement of the unmanned aerial vehicle on the ground observation task in long voyage, the boundary conditions are as follows:
T1＝Tcruising altitude (6)
T4＝TTarget height (7)
h1＝hCruise control system (8)
h2＝h3＝hLowest level of (9)
h4＝hTarget (10)
Wherein, TCruising altitudeFor the ambient temperature, T, of the unmanned aerial vehicle in the cruising phaseTarget heightFor the ambient temperature of the drone in the target area, hCruise control systemAltitude, h, of the cruising flight of the unmanned aerial vehicleLowest level ofFlight altitude h of flat flight section for unmanned aerial vehicleTargetFlying the altitude for the mission of the drone;
step 4, obtaining experience parameter K
Designing a short-distance flight route with a track similar to that of a task preparation stage, carrying out flight correction of the unmanned aerial vehicle, and recording measured values of load temperature and flight altitude in the whole flight process by using a temperature sensor additionally arranged on the load of the unmanned aerial vehicle;
fitting data by using a formula (5) to obtain an empirical parameter K in a general solution;
step 5, calculating the load temperature T of the flight point of the descending section to the horizontal flight section2
Calculating to obtain a load temperature function T of the descending section by using a formula (5), an empirical parameter K and boundary conditions (6), (8) and (9)Descending section(h) Further obtaining the load temperature T of the flight point of the descending section to the level flight section2
Step 6, calculating the load temperature T of the flight point of the horizontal flight section to the ascending section3
Calculating to obtain a load temperature function T of the rising section by using a formula (5), an empirical parameter K and boundary conditions (7), (9) and (10)Rising section(h) Further obtaining the load temperature T of the flight point of the flat flight section to the rising section3；
Step 7, calculating the averageFlight load temperature function TPing Fei(S) and voyage S
For convenience of calculation, at the boundary between the descent segment and the flat flight segment, let s be 0, and use equation (5) and empirical parameter K, T2And T3And calculating to obtain a load temperature function T of the level flight sectionPing Fei(S), further obtaining a horizontal flight segment voyage S, which is as follows:
step 8, obtaining key waypoints of the route
According to the flight course S of the flat flight section obtained in the step 7, the speed vectors of the descending section and the ascending section of the unmanned aerial vehicle are determined by the performance of the unmanned aerial vehicle, and the flight course of the ascending section and the descending section can be obtained as known speed vectors; gradually carrying out reverse thrust by the target waypoint, namely determining a boundary point of the ascending section and the task implementing section, a boundary point of the level flight section and the ascending section, a boundary point of the descending section and the level flight section and a boundary point of the cruise section and the descending section; thus obtaining the positions of 4 key navigation points and unmanned aerial vehicle speed vector information;
step 9, obtaining the flight route of the task preparation stage
And (4) connecting the 4 key navigation point positions and unmanned aerial vehicle speed vector information obtained in the step (8) with a straight line by using two sections of circular arcs, namely obtaining the flight path of the whole task preparation stage.
2. The method for planning the flight path of the long-endurance unmanned aerial vehicle based on the temperature constraint condition as claimed in claim 1, wherein the two arcs are connected with a straight line, and the process of obtaining the flight path in the whole task preparation stage is as follows, P1～P4Respectively 4 key waypoints; o is1～O4Are respectively circles tangent to the velocity vector of the unmanned aerial vehicle at the key navigation point and the radius of the circlesEqual to the circular arc radius of descent or ascent of the drone, this parameter being related to the drone performance and known; v1Cruising speed for the unmanned aerial vehicle; v2For the descending speed of the unmanned aerial vehicle, the vertical component of the unmanned aerial vehicle in the vertical direction is VDescend；V3For the flying speed of unmanned aerial vehicle, i.e. VPing Fei；V4For the ascending speed of the unmanned aerial vehicle, the vertical component of the unmanned aerial vehicle in the vertical direction is VRise up；V5The flight speed of the unmanned aerial vehicle is determined by the load requirement.
3. The method for planning the flight path of the long-endurance unmanned aerial vehicle based on the temperature constraint conditions according to claim 1 or 2, wherein in an actual mission, the empirical parameter K takes the same value in a descending section, a level flight section and an ascending section so as to simplify calculation and improve test efficiency.
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