Flight method of fixed-wing unmanned aerial vehicle for collecting upflow of mountain terrain by utilizing monsoon climate

Abstract

The invention discloses a flying method of a fixed-wing unmanned aerial vehicle for collecting upflow of mountainous terrain by utilizing monsoon climate, which comprises the following steps of: pre-measuring and calculating the wind speed of a region of interest by utilizing a numerical simulation method, and determining a weather condition capable of utilizing the upflow, namely the monsoon speed when the unmanned aerial vehicle just flies without energy consumption; then proper flight time is determined, and flight control parameters of the unmanned aerial vehicle are adjusted by using a PID control method according to a mathematical equation of a dynamic system of the unmanned aerial vehicle, so that the unmanned aerial vehicle can keep stable and horizontal flight, and the course of the unmanned aerial vehicle tends to the opposite direction of monsoon; and in actual flight, an extended Kalman filter is used to estimate the upflow, and the energy gain in the task execution process is analyzed by quantizing flight data. According to the invention, long-endurance flight can be carried out by using upflow, a large amount of resources are saved, the feasibility of collecting wind energy is verified in the flight process, and experience support is provided for developing novel upflow.

Description

Technical Field

[0001] The invention relates to the technical field of rising air flow collection, and in particular to a flying method for a fixed-wing unmanned aerial vehicle to collect rising air flow in mountainous terrain by utilizing monsoon climate. Background Art

[0002] Marine birds such as albatrosses use the shear wind field on the sea surface to fly for long flight times, while birds living in valleys and woods use thermal updrafts caused by temperature differences and dynamic updrafts caused by natural obstacles such as valleys to find food. In natural landforms, updrafts are divided into two categories according to the causes of their generation: thermal updrafts and dynamic updrafts. Thermal updrafts refer to updrafts formed by uneven surface heating due to solar radiation and unstable energy in the atmosphere. Dynamic updrafts and wave updrafts refer to updrafts generated when wind encounters high obstacles such as mountains when flowing horizontally and is forced to move upward along the surface of the hillside. However, the current records of tracking birds in updrafts are concentrated on thermal updrafts, and there are fewer records of dynamic updrafts and wave updrafts. In short, the troposphere is caused by uneven heating of the ground caused by clouds, or uneven pressure fields caused by natural obstacles such as cliffs, mountains and valleys drive the movement of air, which contains various forms of atmospheric energy for use by natural organisms. Effective use of this energy in different flight environments will be a breakthrough in the research of long-flight UAVs.

[0003] The characteristic of small fixed-wing UAVs is that they fly at a low Reynolds number (10 5 Under this flight condition, the ratio of viscous force is large, resulting in a low lift-to-drag ratio of the airfoil. Statistical data of aircraft at different Reynolds numbers show that the maximum lift-to-drag ratio of a conventional airfoil near a low Reynolds number is approximately 6). The range growth of fixed-wing UAVs is greatly limited by the aerodynamic efficiency of the airfoil section, that is, the lift-to-drag ratio of the aircraft. Considering that birds fly at a low speed and are similar in size to small UAVs, many researchers have drawn inspiration from birds in nature and designed flexible wings or deformable wings to improve the lift-to-drag ratio of fixed-wing aircraft under low-speed conditions, so as to further increase the airborne residence time of fixed-wing aircraft under low-speed conditions. The high lift of the wing is achieved by forcing flow separation at the leading edge of the airfoil, and the airfoil with flow separation can withstand gusts and free stream turbulence without sacrificing aerodynamic efficiency, thereby increasing its flight time limit to 4 times that of existing UAVs. In recent years, researchers have focused on developing energy in nature, hoping to bring new hope to the development of long-flight UAVs. There are many forms of energy in nature for us to use, among which flying using solar energy is a typical example. Solar UAVs are becoming increasingly popular with their advantages of long-flight flight, economy and environmental protection. Airbus's "Zephyr S" solar drone reportedly set a record for the longest flight in the Earth's atmosphere after flying in the air for nearly 26 days. However, in order to ensure the use of solar energy and avoid gas disturbances caused by complex weather in the troposphere, long-flight solar drones have to fly at an altitude of tens of thousands of meters. However, there are indeed some solar drones designed to fly at low altitudes. These solar drones are often affected by the weather. When encountering cloudy days, the energy harvesting efficiency of solar cells will drop significantly. Therefore, it is very necessary to find and develop new ways of energy utilization to improve the flight performance of aircraft.

[0004] The problem of thermal updrafts has long been one of the hot research topics for pilots to increase the energy of gliders. At present, many significant progress has been made in actual flight, but there are few ways to soar between valleys using dynamic updrafts. Therefore, the present invention focuses on the dynamic updrafts caused by natural obstacles in valleys. First, the energy utilization of fixed-wing drones in a non-field simulated terrain environment is determined, and then the critical wind speed for glider flight is determined through a series of numerical calculations. The present invention will use numerical simulations to determine the critical conditions for wind energy collection in a non-field environment, and directly use the Global Weather Forecast System (GFS) provided by the Meteorological Bureau to determine whether energy can be obtained from the monsoon, and use the Extended Kalman Filter (EKF) to estimate the updrafts, and use experiments to verify the advantages of collecting updrafts on hillsides. Summary of the invention

[0005] The purpose of the present invention is to address the deficiencies of the prior art and propose a method for a fixed-wing UAV to use the monsoon climate to collect rising air currents in mountainous terrain. The present invention simulates the wind field in a specific area off-site; reconstructs the selected UAV through reverse engineering, and plots the collected energy after interacting with the wind field; determines the critical conditions for collecting wind energy through numerical interpolation; and conducts wind energy acquisition experiments in advance in the GFS according to the weather. This off-site simulation and confirmation of wind energy utilization provides great convenience for gliders to perform tasks in mountainous areas, saving a lot of manpower and time resources.

[0006] The object of the present invention is achieved through the following technical solution: A flying method for a fixed-wing UAV to collect rising air currents in mountainous terrain using monsoon climate, comprising the following steps:

[0007] (1) Extract the three-dimensional terrain data of the hillside impacted by the monsoon in the area of ​​interest from the open geographic information system, then set the incoming wind speed, and then use the large eddy simulation numerical calculation method to calculate the updraft in the area of ​​interest;

[0008] (2) The updraft in the area of ​​interest is input into the simulation system to interact with the UAV, the UAV is used to perform flight simulation in the area of ​​interest, and then the energy gain of the UAV during flight is calculated according to the energy formula;

[0009] (3) By changing the monsoon speed in the simulation system multiple times and performing multiple flight simulations, the energy gain obtained by the UAV during each flight is calculated, and then the relationship between the energy gain obtained by the UAV and the monsoon speed is obtained. The interpolation method is used to find the monsoon speed when the UAV flies without energy consumption as the optimal monsoon speed;

[0010] (4) Based on the relationship between the energy gain obtained by the UAV and the monsoon speed, the mathematical equation of the UAV dynamics system is constructed;

[0011] (5) Check the monsoon speed in the area of ​​interest according to the global forecast system provided by the Meteorological Bureau, and select the flight time according to the optimal monsoon speed; and adjust the flight control parameters of the UAV according to the mathematical equations of the UAV dynamics system so that the UAV can fly stably;

[0012] (6) Based on the flight time and flight control parameters determined in step (5), a flight experiment of the UAV is carried out, and during the experiment, the updraft and the energy state of the UAV are estimated.

[0013] Furthermore, in step (1), when extracting the three-dimensional terrain data of the hillsides impacted by the monsoon in the area of ​​interest from an open geographic information system, it is necessary to import the elevation data into the mapping software and select the hillsides to provide terrain support for the generation of updrafts; wherein the elevation data is obtained by extracting from the open geographic information system.

[0014] Furthermore, in the step (1), when calculating the updraft in the area of ​​interest using the large eddy simulation numerical calculation method, it also includes:

[0015] It is necessary to use real UAV parameters for simulation, then restore the UAV shape through reverse engineering, and then construct the UAV parameters by measuring its parameters. Finally, the aerodynamic coefficient and moment coefficient of the UAV are calculated by the vortex lattice method, and the aerodynamic coefficient and moment coefficient of the UAV are used for simulation to obtain the updraft in the area of ​​interest.

[0016] Furthermore, the energy formula is expressed as:

[0017]

[0018] In the formula, represents the energy gain of the drone, E a represents energy, m is mass, g is gravitational acceleration, D represents resistance, and w z represents the updraft, w x represents the incoming wind speed, γ represents the track angle, V a is the speed relative to the wind, and the superscript · indicates the corresponding derivative.

[0019] Furthermore, the mathematical equation of the UAV dynamics system is expressed as:

[0020]

[0021] In the formula, v a represents the speed relative to the wind, α represents the angle of attack, θ represents the pitch angle, Q represents the angular acceleration, q represents the incoming flow pressure, S represents the wing area, Sc represents the wing area chord length, C T represents the thrust coefficient, C D represents the drag coefficient, C L is the lift coefficient, C m represents the torque coefficient, t represents time, I yy Represents the moment of inertia.

[0022] Furthermore, in step (5), adjusting the flight control parameters of the drone specifically includes:

[0023] The flight control parameters of the UAV are adjusted by using the PID control method so that the UAV can fly stably. When adjusting the flight control parameters, the glider does not require high maneuverability. The core of adjusting the flight control parameters is to ensure that the turbulent wind speed in the high altitude does not affect the normal and stable flight of the UAV.

[0024] Furthermore, in step (6), before conducting the flight experiment of the drone, it is necessary to ensure that the drone can fly, which is specifically determined by the following method: using a handheld airspeed meter to measure the wind speed at the top of the hill. When the wind speed is greater than the theoretically calculated optimal monsoon speed value, it means that the drone can fly, and only then can the flight experiment of the drone be carried out.

[0025] Furthermore, in step (6), estimating the energy state of the updraft and the drone is specifically achieved by the following method:

[0026] First, the wind speed at the top of the hill is measured by a handheld airspeed meter; then the measured wind speed is optimized using an extended Kalman filter to obtain the updraft; finally, the energy gain is calculated based on the updraft using the energy formula, which is the energy state.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] (1) The present invention determines the critical conditions for using drones to collect wind energy in a certain area under the influence of monsoon climate through a numerical simulation method, saving a lot of resources.

[0029] (2) The present invention reverse-engineers existing gliders and determines the feasibility of gliders collecting monsoon climate energy. In this process, no design parameter information or aerodynamic parameters of the glider are required, which provides a paradigm for verifying energy collection by different aircraft.

[0030] (3) Even at relatively low wind speeds, the UAV can collect a certain amount of energy, a characteristic that depends on the aerodynamic characteristics of the fixed wing; when the cruising speed is close to the incoming flow, the glider hovers over the hillside area at an appropriate slope without moving forward, thereby maintaining a constant airspeed and slowly ascending; therefore, the present invention is crucial to improving the endurance of future tests by designing fixed wings suitable for specific terrain.

[0031] (4) The method of the present invention includes: extracting high-precision three-dimensional terrain data and calculating updrafts using a large eddy simulation (LES) numerical calculation method; setting up a drone in the environment to interact with the airflow and estimate the monsoon climate energy collected by the fixed-wing drone; finding the monsoon speed at which the glider can fly without energy consumption; based on the weather conditions predicted by the global weather forecast system provided by the Meteorological Bureau, the updrafts can be estimated through the EKF, a flight experiment can be carried out to estimate the energy state of the real glider, and the method of collecting monsoon climate energy using a fixed-wing drone can be verified. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the specific power and net power of the glider under different speed conditions;

[0033] Figure 2It is the verification framework diagram of the mountaintop flight test;

[0034] Figure 3 It is a schematic diagram of the flight space trajectory of the high-altitude outdoor experiment;

[0035] Figure 4 is the filtered wind direction and glider heading change diagram; where, Figure 4 (a) is the filtered wind direction change diagram, Figure 4 (b) is the heading change diagram of the glider;

[0036] Figure 5 is a diagram of the parameter changes of the glider in the outdoor energy harvesting experiment; Figure 5 (a) is a graph showing the altitude change of the glider during the outdoor energy harvesting experiment. Figure 5 (b) is a graph showing the climbing rate of the glider in an outdoor energy harvesting experiment. Figure 5 (c) is a graph showing the pitch angle variation of the glider during the outdoor energy harvesting experiment;

[0037] Figure 6 is the estimated wind field variation map; where, Figure 6 (a) is the wind field change diagram of the north wind direction in the estimated wind field. Figure 6 (b) is the wind field change diagram of the estimated westerly direction in the wind field. Figure 6 (c) is the velocity variation diagram in the z-axis direction recorded by the flight control barometer;

[0038] Figure 7 It is a time history diagram of specific kinetic energy and specific potential energy during the harvesting process calculated using measured and estimated data; Figure 7 (a) is the specific kinetic energy time course diagram during the entire harvesting process. Figure 7 (b) is the time course diagram of specific potential energy during the entire harvesting process. Figure 7 (c) is the instantaneous specific power calculated during the entire harvesting process, Figure 7 (d) is the time history diagram of the power consumed by the glider's drag during the entire harvesting process. DETAILED DESCRIPTION

[0039] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims. It should be understood that the above general description and the detailed description that follows are merely exemplary and explanatory and cannot limit the present application.

[0040] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0041] It should be understood that, although the term first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of..." or "when..." or "in response to determination". Moreover, the term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process and method including a series of elements include not only those elements, but also include other elements not clearly listed, or also include elements inherent to such process and method. In the absence of more restrictions, the elements limited by the statement "including one..." do not exclude the existence of other identical elements in the process, method, article or equipment including the elements.

[0042] The present invention is described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the features of the following embodiments and implementations can be combined with each other.

[0043] The outstanding advantages of fixed-wing UAVs in terms of speed, maneuverability, and range have expanded their application needs in scientific research. After breaking through the limitation of short range of fixed-wing UAVs, the practical application of UAVs will be further expanded. The present invention aims to increase the flight time of UAVs by collecting updrafts in mountainous areas, where updrafts are the speed of updrafts, which are caused by the monsoon being lifted by the terrain. Fixed-wing UAVs can use updrafts to fly for long flight times.

[0044] Embodiment 1:

[0045] The flying method of the fixed-wing UAV of the present invention for collecting rising air currents in mountainous terrain by utilizing monsoon climate specifically comprises the following steps:

[0046] (1) The three-dimensional terrain data of the hillsides impacted by the monsoon in the area of ​​interest were extracted from the open geographic information system (GIS), and then the incoming wind speed was set, and the updraft in the area of ​​interest was calculated using the large eddy simulation (LES) numerical calculation method.

[0047] It should be understood that by setting the incoming flow conditions (ie, the incoming flow wind speed), the updraft generated by the monsoon affected by the hillside can be calculated, ie, the required updraft in the area of ​​interest.

[0048] Furthermore, when extracting the three-dimensional terrain data of the hillsides impacted by the monsoon in the area of ​​interest from the open geographic information system, it is necessary to import the elevation data into the mapping software, such as pointwise software, to select suitable hillsides to provide good terrain support for the generation of updrafts. The elevation data is obtained by extracting from the open geographic information system.

[0049] Furthermore, when using the LES numerical calculation method to calculate the updraft in the area of ​​interest, it also includes: using real UAV parameters for simulation, then restoring the UAV shape through reverse engineering, and then measuring its parameters to construct the parameters of the UAV, and finally calculating the aerodynamic coefficient and moment coefficient of the UAV through the vortex lattice method, and using the aerodynamic coefficient and moment coefficient of the UAV for simulation to obtain the updraft in the area of ​​interest.

[0050] (2) The updraft in the area of ​​interest is input into the simulation system to interact with the UAV, and the UAV is used to perform flight simulation in the area of ​​interest. Then, the energy gain of the UAV during flight is calculated according to the energy formula.

[0051] Furthermore, the energy formula is expressed as:

[0052]

[0053] In the formula, represents the energy gain of the drone, E a represents energy, m is mass, g is gravitational acceleration, D represents resistance, and w z represents the updraft, w x represents the incoming wind speed, γ represents the track angle, V a is the speed relative to the wind, and the superscript · indicates the corresponding derivative.

[0054] (3) By changing the monsoon speed in the simulation system multiple times and performing multiple flight simulations, the energy gain obtained by the UAV during each flight is calculated, and then the relationship between the energy gain obtained by the UAV and the monsoon speed is obtained. The interpolation method is used to find the monsoon speed when the UAV just flies without energy consumption as the optimal monsoon speed.

[0055] It should be noted that the energy gain obtained by the UAV will change when the monsoon speed in the simulation system is changed. Therefore, by changing the monsoon speed in the simulation system multiple times, performing multiple flight simulations, calculating the energy gain of the UAV corresponding to each flight simulation, and then fitting the relationship, the relationship between the energy gain obtained by the UAV and the monsoon speed is obtained. Further observing the speed range that the net energy passes through, the interpolation method can be used to find the monsoon speed when the UAV just flies without energy consumption.

[0056] (4) Based on the relationship between the energy gain obtained by the UAV and the monsoon speed, the mathematical equation of the UAV dynamics system is constructed.

[0057] Furthermore, the mathematical equation of the UAV dynamics system is expressed as:

[0058]

[0059] In the formula, v a represents the speed relative to the wind, α represents the angle of attack, θ represents the pitch angle, Q represents the angular acceleration, q represents the incoming flow pressure, S represents the wing area, Sc represents the wing area chord length, C T represents the thrust coefficient, C D represents the drag coefficient, C L is the lift coefficient, C m represents the torque coefficient, t represents time, I yy Represents the moment of inertia.

[0060] In the above formula, the force between the drone and the airflow is expressed by the lift coefficient C L and the drag coefficient C D Calculation, which is approximated using the open source software XFLR5. The energy of the drone's interaction with the updraft is calculated using the energy formula.

[0061] (5) Check the monsoon speed of the area of ​​interest according to the Global Forecast System (GFS) provided by the Meteorological Bureau, and select the flight time according to the optimal monsoon speed; and adjust the flight control parameters of the UAV according to the mathematical equations of the UAV dynamics system so that the UAV can fly stably.

[0062] It should be understood that the monsoon speed changes all the time, but the change of monsoon speed within a time period is based on a basis and changes within a certain range. Therefore, the monsoon speed in the area can be checked according to the global forecast system, and then the appropriate flight time can be selected for flight experiments. Specifically, the optimal monsoon speed can be used to determine which time period is the appropriate flight time for the flight experiment.

[0063] Furthermore, the flight control parameters of the UAV are adjusted, specifically including: adjusting the flight control parameters of the UAV by utilizing the PID control method so that the UAV can fly stably; when adjusting the flight control parameters, the glider is not required to have high maneuverability, and the core of adjusting the flight control parameters is to ensure that the turbulent wind speed at high altitude does not affect the normal and stable flight of the UAV.

[0064] It should be understood that when adjusting the flight control parameters of the drone, in addition to enabling the drone to fly stably, the drone's heading can also be made to tend to the opposite direction of the monsoon, which makes it easier to collect wind energy.

[0065] (6) Based on the flight time and flight control parameters determined in step (5), a flight experiment of the UAV is carried out, and during the experiment, the updraft and the energy state of the UAV are estimated.

[0066] Furthermore, before conducting a UAV flight experiment, it is also necessary to ensure that the UAV can fly. This is determined by the following method: Use a handheld airspeed meter to measure the wind speed at the top of the hill. When the wind speed is greater than the theoretically calculated optimal monsoon speed value, it means that the UAV can fly. Only then can the UAV flight experiment, that is, the energy collection experiment, be carried out.

[0067] It should be understood that only when the measured wind speed is greater than the theoretically calculated optimal monsoon speed value can the UAV be ensured to fly; only after ensuring that the UAV can fly can the flight experiment of the UAV be carried out. Energy can be collected during the flight, so the flight experiment can also be considered as an energy collection experiment.

[0068] Furthermore, the energy state of the updraft and the UAV is estimated by the following method: first, the wind speed at the top of the hill is measured by a handheld airspeed meter; then the measured wind speed is optimized using an extended Kalman filter (EKF) to obtain the updraft; finally, the energy gain is calculated according to the updraft using the energy formula, which is the energy state.

[0069] It should be noted that the wind speed measured by the airspeed meter is first used to estimate the updraft and further estimate the energy state. The calculated energy gain is a positive representation of the energy collected by the drone. In addition, the feasibility of wind energy collection is verified during the flight of the drone.

[0070] Embodiment 2:

[0071] The method for flying a fixed-wing UAV using monsoon climate to collect rising air currents in mountainous terrain specifically includes the following steps:

[0072] S1. Inputting the data of interaction between wind field and terrain into the simulation system to interact with the aircraft. The data of interaction between wind field and terrain is the updraft calculated by the LES numerical calculation method in Example 1.

[0073] S2. Explore the critical conditions for the aircraft to fly for a long time without power in natural terrain, simulate the natural wind field characteristics under different speed conditions in the OpenFoam platform, and obtain the corresponding wind field data; then input the wind field data into the simulation system to interact with the aircraft to facilitate flight simulation.

[0074] S3. The incoming wind speed increases, and the flight is maintained at a stable pitch angle. The absolute value of the average power calculated according to the energy utilization principle formula under different speed conditions is plotted, that is, the relationship between energy gain and monsoon speed, to further determine the critical flight condition, that is, the monsoon speed when the aircraft just flies without energy consumption.

[0075] S4. A standard-class glider ASW28 is used as the aircraft described in this embodiment. It has a span of 2.540 meters and is built of modern fiber-reinforced composite materials to verify that the aircraft can obtain energy from the rising air flow in front of the ridge.

[0076] S5. In order to reduce the complexity of the perception system and reduce the weight of the glider flying in the air, this embodiment adopts a method based on an extended Kalman filter, using a GNSS sensor system and a pitot tube to estimate wind field information under complex terrain. As an efficient recursive filter that can estimate the state of a dynamic system from a series of measurements containing noise, EKF is used in the GNSS sensor system to quickly and accurately perform satellite phase attitude determination, and is used to fuse data from different sensors in aircraft attitude estimation. In the flight experiment of this embodiment, the GNSS sensor system is used to provide the speed of the aircraft relative to the inertial coordinate system, and the pitot tube is used to measure the dynamic pressure of the aircraft speed relative to the airflow. Unlike traditional frequency domain filters, the extended Kalman filter is a time domain state predictor that takes into account the errors in the system modeling process and the measurement noise of the sensor system, and models any state space model as follows:

[0077] x k =f(x k-1 )+w k

[0078] z k =h(x k )+v k

[0079] In the formula, x k represents the system state at time k, f represents the system function, and w k represents process noise; z k represents the observation result of the nonlinear measurement function h, v kIndicates the influence of measurement noise and interference. In the experiment of predicting the wind field, it includes: the scale factor γ of the Pitot tube, which is used for real-time calibration and fault diagnosis of the sensor; process noise w k , is a correction to the imperfect mathematical model and system disturbance; k is the observation result of the nonlinear measurement function h, including the influence of measurement noise and interference, expressed as v k Compared with the Pitot tube, the GNSS sensor system can already measure the gliding speed of the glider with high precision and accuracy, so the GPS data information is not considered as observation data here.

[0080] Further obtain the prior estimate of the system state and its error covariance matrix, whose expressions are:

[0081]

[0082] In the formula, Represents a priori estimate of the system state; represents the error covariance matrix of the prior estimate. Since there is no information about the wind field, in this embodiment, the wind field will be considered to be constant over time. Q represents the noise covariance matrix, which represents the error between the state transfer matrix and the actual process. A represents the state transfer matrix of the system, and the superscript T represents the transpose of the matrix.

[0083] S6. By measuring the observed data of the system, the optimal estimate of the system state is obtained to obtain its posterior estimate, which is expressed as:

[0084]

[0085] In the formula, Represents the posterior estimate of the system state, representing the fusion of the system's predicted data and observed data; K k represents the Kalman gain coefficient, which is the intermediate result of filtering and is determined by minimizing the sum of squares of the true state and the estimated state norm; H represents the observation matrix of the system; R represents the covariance matrix of the measurement error, which is related to the measuring instrument.

[0086] S7. Update the error covariance matrix formula of the posterior estimate and use it as the prior estimate input value for the next time step, so that each updated state estimate is calculated from the estimate of the previous time step and the new input data.

[0087] S8. Due to the presence of many unmeasurable and unpredictable turbulences in the atmosphere, the inherent stability of the aircraft and the manual input of the actuator operation are not enough to ensure stable flight under complex working conditions. Uncertain gusts in front of the windward slope of the ridge will make the aircraft uncontrollable. Therefore, a cascade attitude controller is required to convert the roll angle and pitch angle into the input of the actuator to ensure that the aircraft can fly stably outside of visual observation. The outer loop of the controller is composed of a PI controller, which calculates the current angle error to generate the desired pitch angle and roll desired angular velocity input into the inner loop. The inner loop is composed of a PD controller, which inputs a PWM signal to the actuator distributor based on the current angular velocity and the desired angular velocity.

[0088] S9. Referring to step (6) of Example 1, carry out a flight experiment of the aircraft.

[0089] Embodiment 3:

[0090] This embodiment provides a flying method for a fixed-wing UAV to collect rising air currents in mountainous terrain by utilizing monsoon climate.

[0091] The OpenFoam platform simulates the characteristics of natural wind fields under different speed conditions, and the data on the interaction between the wind field and the terrain are input into the simulation environment to interact with the glider. The glider takes off at an altitude of 710m and starts to turn off the power 200m in front of the hillside.

[0092] Figure 1 The average values ​​of the specific power and net power of the glider under different speed conditions are given. Figure 1 The orange line in the figure shows the work done by the updraft on the glider. It can be seen that as the incoming flow speed increases, the updraft formed by the interaction between the terrain and the wind strengthens, and the energy collected increases significantly. Figure 1 It can be seen from the figure that there is no obvious correlation between drag and wind speed, which is reasonable because the airspeed required for stable ascent or soaring in the air is limited. At the same time, the increase in incoming flow speed has a much greater impact on ground speed than on airspeed. It is worth noting that Figure 1 The yellow and purple lines in are almost zero, which means that the work of horizontal time-varying wind and vertical time-varying wind is negligible, so the two lines almost overlap. Figure 1 The red line in is the net power, indicating that when the ambient wind speed is greater than 6m / s, the glider can fly for a long time without power. It can be seen that the critical speed is very small. The fundamental reason may be that the effects of the fuselage, tires, engine and propeller are ignored in the current simulation. Therefore, the critical incident speed can be used as a reference for comparison with the weather forecast data of the Meteorological Bureau to prepare for the flight experiment on the mountain. The specific power lines of horizontal time-varying wind and vertical time-varying wind coincide because they both tend to zero, such as Figure 1 As shown in the red dashed box.

[0093] When the incoming flow speed increases again, although the glider maintains a stable pitch angle, the updraft increases the glider's local angle of attack, causing the glider's energy to grow steadily. In addition, since the glider takes off from a hillside with strong airflow, when the incoming flow speed is high, the glider's airspeed remains unchanged, but it is affected by the wind ahead and the glider's aerodynamic characteristics. The glider cannot penetrate the wind field and stays in an area with strong updrafts, rising at a stable climb rate.

[0094] The energy harvesting mechanism is evaluated through flight experiments. The flight test framework in outdoor environment is as follows Figure 2 The key factor for energy harvesting is wind field estimation. Specifically, the wind speed is estimated by combining the EKF with the state information of the glider and the airspeed measured by the onboard avionics system. During the flight, a PID flight controller is used to consider the yaw stability of the glider.

[0095] A 13*6.5 propeller equipped with a 1000KV Sunnysky X2814 motor is installed on the nose of the glider, enabling the glider to soar in strong wind fields. An inertial measurement unit (IMU) and a magnetometer are embedded to estimate the ground position and attitude angle. Similarly, the height relative to the sea level is measured by a barometer, and the GPS provides sufficiently accurate ground speed information. The avionics systems shown in Table 1 are integrated into the autopilot CUAV V5+.

[0096] Table 1: Various avionics systems

[0097] equipment describe Autopilot CUAV V5+ Microcontroller Arm Cortex M7 Barometer MS5611 GPS Neo-M8N Accelerometer / gyroscope ICM-20689 Brushless Motor 1000KV

[0098] Next, the energy gain will be evaluated using flight experiment data and estimated wind fields to assess the potential benefits of flying a glider unpowered in hillside updrafts.

[0099] The outdoor test site is located at the top of the hillside (30°30'34.32"N, 119°47'50.00"E), where the climate is subtropical monsoon. Under the influence of high pressure, cold northwest winds frequently develop in winter, creating conditions for the formation of updrafts on the windward slope. The GFS weather forecast run by the Meteorological Bureau shows that the wind speed during the test period is 3.85m / s, which provides good conditions for energy harvesting verification.

[0100] The trajectory of the glide is shown in the figure Figure 3 As shown, the red triangle represents the beginning of the glider collecting energy from the updraft, while the red five-pointed star represents the end point. Figure 3 The upper right corner of the diagram shows the eastern and northern trajectories of the process. Figure 3 The black arrow in the figure indicates that the wind direction is northwest.

[0101] Figure 4 (a) shows the wind direction estimated based on the Kalman filter, which increases slightly before 8.1s and then remains constant at around 28°; after 26.60s, the direction gradually decreases, which is basically consistent with the data from the ECMWF Weather Forecast Center. In general, the glider experiences almost the same wind direction. Figure 3 The top right corner of the figure shows a top view of the trajectory, indicating that the glider is moving in a southwest direction. The heading angle is estimated by the attitude and heading reference system (AHRS). Figure 4 As shown in (b), although the flight path is not along the incoming wind, it tends to be aligned with the wind direction. During the period from 8.1s to 26.6s, due to the increase in wind direction, the heading angle increases, and the vertical tail changes the heading angle, thereby eliminating the sideslip.

[0102] The glider took off from near the top of a mountain at an absolute altitude of 712m. It started climbing slowly, but it accelerated significantly around 6 seconds and 14 seconds. Figure 5 (a). The climb rate and pitch angle are Figure 5 (b) and Figure 5 As shown in (c), although the pitch angle is always negative, which will cause a rapid sinking, the updraft steadily lifts the glider; another important reason that must be mentioned is that the angle of incidence of the wing is about 7° to keep the angle of attack positive. It is worth noting that the throttle is almost zero throughout the process, except for a slight input in the first 3 seconds. GPS data shows that the glider reached a maximum altitude of about 742 meters without support from the power system. This potential energy benefit is well worth the development of an effective and mature control system that relies on real-time sensing of airflow. Figure 5 The orange line in the figure represents the throttle input, and the entire process is considered as unpowered flight, although there is a slight throttle input of less than 20% outside the first 3 seconds, which can be ignored.

[0103] The north wind direction estimated by the glider is Figure 6 As shown in (a), the negative signal indicates that the wind was blowing from the south, with an average wind speed of 4.80 m / s. Figure 6 In (b), the initial speed is about 9 m / s. Due to the slow climb in altitude, the initial speed increases slightly, and the average wind speed reaches 10.94 m / s, which is larger than the data from the ECMWF Weather Forecast Center. In the estimated data, such as 6.5s, 17s, 22s or 26s, there are mutations, which can explain the pulsation of wind shear or turbulence. These data enable the wind field in the NED coordinate system to be estimated by the wind speed measured by EKF and GPS.

[0104] Figure 6(c) is the speed in the z-axis direction recorded by the flight control barometer, where the blue line represents the estimated vertical airflow and the negative value indicates an upward airflow of about 4 m / s at 0-3s and 7-10s. At around 14s and 22s, the updraft is less obvious, resulting in a slight downward motion. As shown in the simulation above, the updraft perceived by the glider weakens as it rises and moves away from the slope. Each time the ground speed tends to be negative, the glider is again affected by a larger updraft to make up for the previous energy loss and ensure a continuous upward state throughout the process.

[0105] like Figure 7 As shown, the red line represents the instantaneous energy of the updraft, the orange area is the collected energy, and the blue area at the bottom is the energy consumed by the glider. The simulation results show that the energy gain and loss mainly come from the updraft and induced drag and viscous drag; the effect of time-varying wind on energy is uncertain, which may lead to energy increase or decrease, or may offset each other; however, in either case, the impact is negligible over a long period of time.

[0106] Figure 7 (c) is the calculated instantaneous specific power. As mentioned above, the sudden change is caused by the pulsation of shear wind. Figure 7 The area enclosed by the red line in (c) and the horizontal and vertical coordinates are the integration of the energy associated with the updraft. To conservatively estimate the efficiency of flying up the hill, the power consumed is determined using the drag generated by the critical stall and the maximum output of the actuators. The power consumed by the glider's drag is obtained as Figure 7 (d) as shown.

[0107] Except for 15s and 20.4s, when the power consumed is slightly greater than the energy gained from the updraft, the net power is positive most of the time, e.g. Figure 7 (a) and Figure 7 (b) as shown. Figure 7 (a) and Figure 7 (b) is the specific kinetic energy and specific potential energy time course of the whole process, from which it can be seen that the specific kinetic energy relative to the airspeed at the initial moment is 97.35 J / kg, which decreases to 76 J / kg, and the specific potential energy reaches 396.93 J / kg at the end. In summary, the total energy increases by 242.32 J / kg, a total increase of 104.85%, which is very consistent with the result calculated by the formula, and its net value is 256 J / kg, where the negligible error may be related to the neglect of time-varying wind.

[0108] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for a fixed-wing UAV to fly a mountain terrain using monsoon climate to collect rising air currents, characterized in that: The following steps are involved: (1) Extract the three-dimensional terrain data of the hillside impacted by the monsoon in the area of ​​interest from the open geographic information system, then set the incoming wind speed, and then use the large eddy simulation numerical calculation method to calculate the updraft in the area of ​​interest; (2) The updraft in the area of ​​interest is input into the simulation system to interact with the UAV, the UAV is used to perform flight simulation in the area of ​​interest, and then the energy gain of the UAV during flight is calculated according to the energy formula; (3) By changing the monsoon speed in the simulation system multiple times and performing multiple flight simulations, the energy gain obtained by the UAV during each flight is calculated, and then the relationship between the energy gain obtained by the UAV and the monsoon speed is obtained. The interpolation method is used to find the monsoon speed when the UAV flies without energy consumption as the optimal monsoon speed; (4) Based on the relationship between the energy gain obtained by the UAV and the monsoon speed, the mathematical equation of the UAV dynamics system is constructed; (5) Check the monsoon speed in the area of ​​interest according to the global forecast system provided by the Meteorological Bureau, and select the flight time according to the optimal monsoon speed; and adjust the flight control parameters of the UAV according to the mathematical equations of the UAV dynamics system so that the UAV can fly stably; (6) Based on the flight time and flight control parameters determined in step (5), a flight experiment of the UAV is carried out, and during the experiment, the updraft and the energy state of the UAV are estimated.

2. The method for flying a fixed-wing UAV using monsoon climate to collect rising air currents in mountainous terrain according to claim 1, characterized in that: In the step (1), when extracting the three-dimensional terrain data of the hillsides impacted by the monsoon in the area of ​​interest from the open geographic information system, it is necessary to import the elevation data into the mapping software and select the hillsides to provide terrain support for the generation of updrafts; wherein the elevation data is obtained by extracting from the open geographic information system.

3. The method for flying a fixed-wing UAV using monsoon climate to collect rising air currents in mountainous terrain according to claim 1, characterized in that: In the step (1), when calculating the updraft in the area of ​​interest using the large eddy simulation numerical calculation method, the method further includes: It is necessary to use real UAV parameters for simulation, then restore the UAV shape through reverse engineering, and then construct the UAV parameters by measuring its parameters. Finally, the aerodynamic coefficient and moment coefficient of the UAV are calculated by the vortex lattice method, and the aerodynamic coefficient and moment coefficient of the UAV are used for simulation to obtain the updraft in the area of ​​interest.

4. The method for flying a fixed-wing UAV using monsoon climate to collect rising air currents in mountainous terrain according to claim 1, characterized in that: The energy formula is expressed as: In the formula, represents the energy gain of the drone, E a represents energy, m is mass, g is gravitational acceleration, D represents resistance, and w z represents the updraft, w x represents the incoming wind speed, γ represents the track angle, V a is the speed relative to the wind, and the superscript · indicates the corresponding derivative.

5. The method for flying a fixed-wing UAV using monsoon climate to collect rising air currents in mountainous terrain according to claim 1, characterized in that: The mathematical equation of the UAV dynamics system is expressed as: In the formula, v a represents the speed relative to the wind, α represents the angle of attack, θ represents the pitch angle, Q represents the angular acceleration, q represents the incoming flow pressure, S represents the wing area, Sc represents the wing area chord length, C T represents the thrust coefficient, C D represents the drag coefficient, C L is the lift coefficient, C m represents the torque coefficient, t represents time, I yy Represents the moment of inertia.

6. The method for flying a fixed-wing UAV using monsoon climate to collect rising air currents in mountainous terrain according to claim 1, characterized in that: In step (5), adjusting the flight control parameters of the drone specifically includes: The flight control parameters of the UAV are adjusted by using the PID control method so that the UAV can fly stably. When adjusting the flight control parameters, the glider does not require high maneuverability. The core of adjusting the flight control parameters is to ensure that the turbulent wind speed in the high altitude does not affect the normal and stable flight of the UAV.

7. The method for flying a fixed-wing UAV using monsoon climate to collect rising air currents in mountainous terrain according to claim 1, characterized in that: In step (6), before conducting the flight experiment of the drone, it is necessary to ensure that the drone can fly, which is specifically determined by the following method: using a handheld airspeed meter to measure the wind speed at the top of the hill. When the wind speed is greater than the theoretically calculated optimal monsoon speed value, it means that the drone can fly, and only then can the flight experiment of the drone be carried out.

8. The method for flying a fixed-wing UAV using monsoon climate to collect rising air currents in mountainous terrain according to claim 1, characterized in that: In step (6), estimating the energy state of the updraft and the drone is specifically achieved by the following method: First, the wind speed at the top of the hill is measured by a handheld airspeed meter; then the measured wind speed is optimized using an extended Kalman filter to obtain the updraft; finally, the energy gain is calculated based on the updraft using the energy formula, which is the energy state.

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