Flight planning method for single microwave radiation-driven UAV with optimal energy utilization

Abstract

The present invention proposes a single microwave radiation driven unmanned aerial vehicle (UAV) flight planning method with optimal energy utilization, comprising the following steps: Step 1: for a given UAV, obtaining basic design parameters, initial state parameters, and a lift-to-drag ratio relationship of the UAV, and using an aircraft performance estimation method to calculate the climb angle boundary and the flight speed boundary of the UAV; Step 2: establishing a mathematical relationship between the UAV position, roll angle, pitch angle, yaw angle, and the energy consumption of the UAV at the current time step; Step 3: based on the basic design parameters and initial state parameters of the UAV, starting from the initial state, calculating the position, yaw angle, and flight speed of the UAV at the next time step; based on the mathematical relationship established in Step 2 and the minimum energy consumption in the current time step, obtaining the roll angle and pitch angle of the UAV at the next time step, and recording the position, attitude angle, flight speed, and energy consumption of the UAV at each time step until the flight mission is finally completed.

Description

Technical Field

[0001] The present invention relates to the fields of new energy, path planning and energy management for aviation vehicles, and specifically to a flight planning method for a single microwave radiation-driven unmanned aerial vehicle (UAV) with optimal energy utilization. Background Art

[0002] Microwave-powered drones convert electrical energy from DC to microwaves via a microwave generator at the transmitter end. These microwaves are then transmitted into free space via an antenna. The drone's rectenna receives and rectifies the microwaves, converting them into DC energy for the drone to use. If component wear and lifespan are not a concern, microwave-powered drones can achieve unlimited flight durations powered by ground-based energy, significantly increasing their payload capacity.

[0003] When a single-base-station ground base station is used for power supply, the energy of the UAV is provided by the ground, and the flight posture of the aircraft during the execution of the operation mission will affect the receiving projection area of ​​the microwave energy, thereby interfering with the microwave energy reception efficiency, resulting in low efficiency of microwave wireless energy transmission, and sometimes even affecting the flight performance of the UAV, resulting in abnormal flight.

[0004] Currently, domestic research on energy management and path planning methods for microwave-powered UAVs primarily focuses on hardware optimization at the receiving end of microwave-powered UAVs. For example, the paper "Modeling and Multi-Objective Optimization of Microwave Wireless Energy Transfer Links for UAV Powering" (Song Yuanming, Master's thesis, National University of Defense Technology, 2020) proposes a modeling and optimization method for microwave wireless energy transfer links for UAV powering. The paper "Research on DC Synthesis Technology of Diode Rectifier Circuits and Design of High-Power Transistor Rectifier Circuits" (Song Dejun, Master's thesis, Xidian University, 2022) investigates the equivalent model construction and high-efficiency array design of rectifier circuits used for wireless powering aircraft. The paper "Design of Ultra-Thin Rectennas for Aircraft" (Yan Yuheng, Master's thesis, University of Electronic Science and Technology of China, 2022) addresses the design of ultra-thin receiving rectennas for aircraft. These hardware-based approaches to improving the performance of microwave-powered UAVs fail to consider the loss of energy transfer projected area during actual flight due to changes in flight attitude, which can reduce energy transfer efficiency. Summary of the Invention

[0005] To solve the above problems, the present invention proposes a single microwave radiation-driven UAV flight planning method with optimal energy utilization. By establishing a mathematical relationship between the UAV's position coordinates, roll angle, pitch angle, yaw angle and microwave power supply, the energy consumption of the UAV at the current time step can be calculated based on the UAV's position coordinates, roll angle, pitch angle and yaw angle at the current time step; by establishing a flight dynamics model of the UAV, the UAV's position coordinates, yaw angle, flight speed and roll angle and pitch angle corresponding to the lowest energy consumption at each time step under a set flight mission are calculated; the obtained UAV position coordinates, roll angle, pitch angle, yaw angle and flight speed at each time step are the optimal flight planning scheme for energy utilization under the set flight mission.

[0006] The technical solution of the present invention specifically includes the following steps:

[0007] Step 1: Establish an atmospheric environment model based on the International Standard Atmosphere. For a given UAV, obtain the basic design parameters, initial state parameters, and lift-to-drag ratio relationship of the UAV. Use the aircraft performance estimation method to calculate the climb angle and flight speed boundaries of the UAV under the set flight mission.

[0008] Step 2: Establish a mathematical relationship between the drone's position coordinates, roll angle, pitch angle, yaw angle, and the microwave energy supplied by a single microwave radiation source. Calculate the drone's energy consumption at the current time step based on the drone's position coordinates, roll angle, pitch angle, and yaw angle at the current time step through the mathematical relationship.

[0009] Step 3: Establish a flight dynamics model. Based on the basic design parameters and initial state parameters of the UAV, according to the set flight mission and time step, starting from the initial state, calculate the position coordinates, yaw angle, and flight speed of the UAV in the next time step; based on the mathematical relationship established in step 2 and the minimum energy consumption of the current time step, obtain the roll angle and pitch angle of the UAV in the next time step until the flight mission is finally completed, and record and store the position coordinates, attitude angle, flight speed, energy consumption, and total energy consumption of the UAV in each time step.

[0010] Furthermore, the basic design parameters of the drone in step 1 include the gravity of the drone , the quality of the drone , UAV wing area , UAV motor power , UAV zero lift drag , the maximum lift coefficient of the UAV , the maximum capacity of drone batteries , inducing factor ; Maximum receiving energy area of ​​the drone ; Climb angle of attack , cruise angle of attack , cruising altitude ;

[0011] The initial state parameters include the initial time , time step , the initial position coordinates of the drone , initial pitch angle , initial yaw angle , initial roll angle , initial climb angle , initial flight speed ,initial Directional speed ,initial Directional speed ,initial Directional speed , the initial output power of the ground energy transmitting base station , initial battery charge ;Location coordinates of ground energy transmitting base station ;

[0012] The lift-to-drag ratio relationship of the UAV refers to the lift-to-drag ratio of the UAV and height , pitch angle , roll angle The mathematical form of the relationship is as follows:

[0013]

[0014] in It is in functional form and is determined by the aerodynamic performance of a given UAV.

[0015] Furthermore, step 1 specifically includes the following sub-steps:

[0016] Step 1.1: Establish an atmospheric environment model based on the International Standard Atmosphere;

[0017] Step 1.2: Calculate the flight speed limit of the drone;

[0018] According to the two intersection points of the UAV's required power curve and available power curve, use the formula

[0019]

[0020] Solve and obtain the two speed values ​​corresponding to the two intersection points of the required power curve and the available power curve , respectively the minimum speed and maximum speed during level flight; is the local atmospheric density determined by the atmospheric environment model, is the flight speed of the drone, Take the intersection value of the required power curve and the available power curve;

[0021] The minimum speed calculated by the above formula is equal to the stall speed Perform a second comparison and take the smaller value as the minimum speed for level flight:

[0022]

[0023] Then the velocity boundary of the UAV is obtained as follows:

[0024] ;

[0025] Step 1.3: Calculate the climb angle boundary of the UAV;

[0026] From the ground to the aircraft's cruising altitude The altitude range is divided into a set number of altitude intervals. In each altitude interval, assuming that the climbing angle range remains unchanged within this altitude interval, the left boundary of the altitude interval is taken as the current climbing altitude, and the climbing angle range of the altitude interval is obtained by using a graphical method. , as the climb angle range for this altitude interval.

[0027] Furthermore, a graphical method is used to obtain the climbing angle range for each altitude interval. The specific process is:

[0028] Assume that the UAV is climbing at the current climbing height with a climbing angle Perform steady climb and obtain the following according to the dynamic equation:

[0029]

[0030]

[0031]

[0032] Where, is the pulling force of the drone, For the lift of the drone, For the resistance of the drone, is the gravity of the drone, is the climbing angle of the UAV, For the quality of the drone, is the flight speed of the drone, is the curvature radius of the UAV’s trajectory;

[0033] Combining the above formulas, we can get the climb rate for:

[0034]

[0035] Get the climb angle:

[0036]

[0037] The resistance calculation expression

[0038]

[0039] Substituting into the climb rate Evaluating the expression yields:

[0040]

[0041] Use the graphical method to solve the above equations, that is, Plot for the independent variable The function graph is within the velocity boundary of the UAV obtained in step 1.2, and the The minimum speed on the function graph of The slope of the line connecting the corresponding point and the origin is the minimum climbing angle ; Maximum climb angle Determined according to the actual carrying capacity of the UAV.

[0042] Furthermore, the specific process of step 2 to establish the mathematical relationship between the drone's position coordinates, roll angle, pitch angle, yaw angle and microwave energy supply is as follows:

[0043] First, establish the coordinate transformation relationship from the navigation axis system to the body axis system; the coordinate origin of the body axis system is located at the center of gravity of the aircraft, The axis is located in the plane of symmetry of the aircraft, parallel to the axis of the fuselage, and points forward. The axis lies in the plane of symmetry of the aircraft and is perpendicular to The axis points downward. The axis is perpendicular to the symmetry plane and points to the right, satisfying the right-hand system; the navigation axis system is the ground inertial coordinate system, and the coordinate origin is the absolute coordinate (0,0,0);

[0044] Based on the coordinates of the drone's location at the current time step and the location of the ground energy transmitting base station , obtain the normal vector of the energy irradiation surface:

[0045]

[0046] Let the initial axis matrix of the drone be:

[0047]

[0048] Then the body axis matrix after the transformation matrix is:

[0049]

[0050] 、 、 They are respectively the navigation axis system and the body axis system for The transformation matrix of the direction, The transformation matrix of the direction and the The transformation matrix of the direction;

[0051] drone body The plane is the receiving surface, and the normal direction of the receiving surface in the body axis system is Direction vector , after transformation, the normal vector of the receiving surface at the current time step is obtained:

[0052] ,

[0053] Where, 、 、 They are the three components of the normal vector of the receiving surface at the current time step;

[0054] The following formula is used to calculate the effective energy receiving area of ​​the UAV for the ground energy transmitting base station after considering the attitude change at the current time step: :

[0055]

[0056] Where, is the maximum energy receiving area of ​​the UAV;

[0057] Then the following formula is used to calculate the receiving efficiency of the energy transmitted by the ground energy transmitting base station at the current time step: :

[0058]

[0059] Where, is the initial output power of the ground energy transmitting base station;

[0060] Then the following formula is used to calculate the energy consumption of the UAV at the current time step:

[0061]

[0062] Where, The maximum capacity of the drone battery.

[0063] Furthermore, step 3 specifically includes the following sub-steps:

[0064] Step 3.1: Based on the aircraft's altitude Calculate the corresponding atmospheric density ;

[0065] Step 3.2: Calculate the pulling force of the drone at the current time step , lift and resistance ;

[0066] Step 3.3: Based on the force acting on the drone, calculate the acceleration of the drone at the current time step;

[0067] Step 3.4: Based on the acceleration of the drone in the current time step, calculate the yaw angle, flight speed, and position coordinates of the drone in the next time step;

[0068] Step 3.5: Energy consumption of the drone based on the current time step Minimum, calculate the roll angle and pitch angle of the drone in the next time step;

[0069] Based on the roll angle of the current time step and the climb angle boundary calculated in step 1.3, the optional ranges of the pitch angle and roll angle at the next time step are established as follows:

[0070] ϕ range ∈[ϕ-∆ϕ,ϕ+∆ϕ]

[0071] γ range ∈[ γ min , γ max ]

[0072]

[0073] Where, 、 is the optional range of the roll angle and climb angle for the next time step, is the set roll angle change; is the angle of attack of the UAV at the current time step, when hour, ,when hour, , where is the climb angle of attack, is the cruise angle of attack;

[0074] for and , randomly in 、 Each sample G samples, forming G The matrix of G is converted into G using the mathematical relationship established in step 2. Energy consumption of the drone corresponding to G combinations at the current time step Calculate and compare, select The minimum value corresponds to and As the roll and pitch angles for the next time step;

[0075] Step 3.6: Update the current time , record and store the position coordinates, attitude angle, flight speed, and energy consumption of the drone at each time step, jump to step 3.1, and repeat the above process until the set flight mission is completed; the energy consumption of the drone at each time step Perform superposition and summation to obtain the energy consumption of the entire UAV flight mission , record and store total energy consumption .

[0076] Furthermore, in step 3.2, the pulling force of the drone at the current time step is calculated , lift and resistance The process is:

[0077] Make the flight speed , according to the UAV motor power , calculate the pulling force of the drone at the current time step :

[0078]

[0079] Zero lift drag of the drone based on the initial parameters of the drone state , induction factor , the gravity of the drone , UAV wing area Atmospheric density corresponding to the current altitude , flight speed , calculate the drag of the drone at the current time step :

[0080]

[0081] According to the current time of the drone's altitude , pitch angle , roll angle , based on the lift-to-drag ratio relationship of the drone, the calculated lift-to-drag ratio of the drone is , and then calculate the lift of the drone in the current time step :

[0082]

[0083] At the initial moment, the height , pitch angle , roll angle .

[0084] Furthermore, in step 3.3, the process of calculating the acceleration of the drone at the current time step based on the force acting on the drone is as follows:

[0085] According to Newton's second law, the UAV's current time step is obtained The axial accelerations are:

[0086]

[0087]

[0088]

[0089] Where, Indicates drone Toward acceleration, Indicates drone Toward acceleration, Indicates drone Toward acceleration;

[0090] If the current flight speed exceeds the speed limit of the UAV determined in step 1.2, the acceleration of the UAV at the current time step is regulated as follows:

[0091]

[0092]

[0093]

[0094] , , is the set acceleration control parameter.

[0095] Furthermore, in step 3.4, based on the acceleration of the drone at the current time step, the process of calculating the yaw angle, flight speed, and position coordinates of the drone at the next time step is as follows:

[0096] Based on the flight speed of the current time step, the yaw angle at the next moment is calculated by the following formula for:

[0097]

[0098] Where, 、 、 are the UAV’s current time step. The velocity of the direction, at the initial moment, , , ;

[0099] Assume that the UAV performs uniform acceleration in a time step. Based on the acceleration and velocity of the UAV in the current time step, the velocity of the UAV in the next time step can be calculated by the following formula:

[0100]

[0101]

[0102]

[0103] Where, is the set time step, 、 、 are the UAVs at the next time step. Speed ​​of direction;

[0104] The displacement of the drone at the current time step is calculated by the following formula:

[0105]

[0106]

[0107]

[0108] Where, 、 、 are the UAV’s current time step. displacement to the direction;

[0109] Then the position coordinates of the drone in the next time step are calculated by the following formula:

[0110]

[0111]

[0112]

[0113] Where, 、 、 They are the position coordinates of the drone at the current time step, and at the initial moment , , ; 、 、 are the position coordinates of the UAV in the next time step, As the altitude of the drone at the next time step.

[0114] Beneficial effects:

[0115] The present invention provides a single microwave radiation driven unmanned aerial vehicle (UAV) flight planning method with optimal energy utilization. By establishing a mathematical relationship between the UAV's position coordinates, roll angle, pitch angle, yaw angle and microwave energy supply, the energy consumption of the UAV at the current time step can be calculated based on the UAV's position coordinates, roll angle, pitch angle and yaw angle at the current time step; by establishing a flight dynamics model of the UAV, the position coordinates, yaw angle, flight speed of the UAV at each time step under a set flight mission and the roll angle and pitch angle corresponding to the lowest energy consumption are calculated; the obtained UAV position coordinates, roll angle, pitch angle, yaw angle and flight speed at each time step are the optimal flight planning scheme for energy utilization under the set flight mission; the present invention can effectively avoid microwave energy supply loss caused by attitude changes of the UAV during actual flight by optimizing the attitude with the lowest energy consumption, thereby effectively improving energy utilization, and can simultaneously record the optimal attitude angle history, energy consumption history and trajectory of the UAV. BRIEF DESCRIPTION OF THE DRAWINGS

[0116] Figure 1 This is a flowchart for implementing an embodiment of the present invention;

[0117] Figure 2 This is a schematic diagram of calculating the maximum and minimum speeds based on a graphical method of required power and available power according to an embodiment of the present invention;

[0118] Figure 3 This is a schematic diagram of the aircraft speed boundary according to an embodiment of the present invention;

[0119] Figure 4 A schematic diagram of solving the minimum climb angle based on a graphical method according to an embodiment of the present invention;

[0120] Figure 5 Schematic diagram of the body axis system according to an embodiment of the present invention;

[0121] Figure 6 is the pitch angle history of an embodiment of the present invention;

[0122] Figure 7 is the roll angle history of an embodiment of the present invention;

[0123] Figure 8 is the yaw angle history of an embodiment of the present invention;

[0124] Figure 9 The flight trajectory of the UAV according to an embodiment of the present invention;

[0125] Figure 10This is a comparison chart of the minimum energy consumption output achieved based on the optimization model and the energy consumption output without considering the influence of posture in an embodiment of the present invention. DETAILED DESCRIPTION

[0126] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood and to enable those skilled in the art to better understand the solutions of the present invention, the present invention is further described and fully explained below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only intended to illustrate the present invention and are not intended to limit the present invention.

[0127] This embodiment takes a certain type of microwave powered UAV as an example, based on a single ground energy transmitting base station power supply scenario, and adopts the method proposed in the present invention to perform flight planning for this type of UAV based on the optimal energy utilization under a set flight mission. In this embodiment, the set flight mission is that the UAV takes off from the ground and climbs to a cruising altitude. 18000m.

[0128] like Figure 1 As shown, the energy utilization-optimized single microwave radiation-driven UAV flight planning method of this embodiment includes the following steps:

[0129] Step 1: Establish an atmospheric environment model based on the International Standard Atmosphere. For a given UAV, obtain the basic design parameters, initial state parameters, and lift-to-drag ratio relationship of the UAV. Use the aircraft performance estimation method to calculate the climb angle and flight speed boundaries of the UAV under the set flight mission.

[0130] Step 2: Establish a mathematical relationship between the drone's position coordinates, roll angle, pitch angle, yaw angle, and the microwave energy supplied by a single microwave radiation source. Through this mathematical relationship, the energy consumption of the drone at the current time step can be calculated based on the drone's position coordinates, roll angle, pitch angle, and yaw angle at the current time step.

[0131] Step 3: Establish a flight dynamics model. Based on the basic design parameters and initial state parameters of the UAV, according to the set flight mission and time step, starting from the initial state, calculate the position coordinates, yaw angle, and flight speed of the UAV in the next time step; based on the mathematical relationship established in step 2 and the minimum energy consumption of the current time step, obtain the roll angle and pitch angle of the UAV in the next time step until the flight mission is finally completed, and record and store the position coordinates, attitude angle, flight speed, energy consumption, and total energy consumption of the UAV in each time step.

[0132] In this embodiment, the basic design parameters of the drone in step 1 include the gravity of the drone , the quality of the drone , UAV wing area , UAV motor power , UAV zero lift drag , the maximum lift coefficient of the UAV , the maximum capacity of drone batteries , inducing factor ; Maximum receiving energy area of ​​the drone ; Climb angle of attack , cruise angle of attack , cruising altitude ;

[0133] In this embodiment, the gravity of the drone =3000N, the mass of the drone =306.12kg, UAV wing area =50m 2 , UAV motor power =7.9KW, UAV zero lift resistance =0.0085, the maximum lift coefficient of the UAV =0.725, the maximum capacity of the drone battery =61200000Wh, induction factor =0.05; UAV maximum receiving energy area =17m 2 ; Climb angle of attack =2°, cruise angle of attack =2°, cruising altitude =18000m;

[0134] The initial state parameters include the initial time , time step , the initial position coordinates of the drone , initial pitch angle , initial yaw angle , initial roll angle , initial climb angle , initial flight speed ,initial Directional speed ,initial Directional speed ,initial Directional speed , initial battery charge ;Location coordinates of ground energy transmitting base station ;

[0135] In this embodiment, the initial time =0s, time step =0.3s, initial coordinate position of the drone =200m, =300m, =500m, initial pitch angle =4°, initial yaw angle =35°, initial roll angle =20°, initial climb angle =2°, initial flight speed =10.3m / s, initial Directional speed =9.67m / s, initial Directional speed =3.52m / s, initial Directional speed =0.36m / s, initial output power of the ground energy transmitting base station =1.7KW, initial battery capacity =1, coordinate position of ground energy transmitting base station 、 、 ;

[0136] The lift-to-drag ratio relationship of the UAV refers to the lift-to-drag ratio of the UAV and height , pitch angle , roll angle The mathematical form of the relationship is as follows:

[0137]

[0138] in It is in functional form and is determined by the aerodynamic performance of a given UAV;

[0139] In this embodiment, the relationship between the lift-to-drag ratio of the drone and the altitude, pitch angle, and roll angle is as follows. This formula is obtained by fitting the aerodynamic performance of the given drone according to conventional aircraft performance calculation methods known in the art:

[0140] .

[0141] In this embodiment, the process of calculating the climb angle boundary and the flight speed boundary of the UAV under the set flight mission using the aircraft performance estimation method in step 1 specifically includes the following sub-steps:

[0142] Step 1.1: Establish an atmospheric environment model based on the International Standard Atmosphere;

[0143] Specifically: Take the sea level reference temperature = 288.15K, the sea level reference pressure = 101325N / m 2 , standard gravitational acceleration g=9.80665Kg / m 2, the temperature and pressure at different altitudes are determined by the standard formula in the table below, where is the aircraft's altitude;

[0144] Table 1 Temperature and pressure formulas at different altitudes

[0145]

[0146] After determining the temperature and pressure from the altitude, the local atmospheric density can be obtained from the following formula: :

[0147]

[0148] In the formula, the constant , is the absolute temperature, is the atmospheric pressure;

[0149] Step 1.2: Calculate the velocity boundary of the UAV;

[0150] At a given altitude, the aircraft's available power Almost unchanged with speed, but the power required As the speed increases, it first decreases and then increases. Using the two intersection points of the required power curve and the available power curve, as shown in Figure 2 As shown, find the maximum and minimum speeds of the aircraft, specifically:

[0151] according to = , the mathematical relationship satisfied by the flight speed is as follows:

[0152]

[0153] in Take the intersection value of the required power curve and the available power curve, is the flight speed of the UAV. Solving the above equation, we can get the two speed values ​​corresponding to the two intersection points of the required power curve and the available power curve. , respectively the minimum and maximum speeds during level flight;

[0154] Since the UAV has a stall speed, the minimum speed and the stall speed are compared twice, and the smaller value is taken as the minimum speed for level flight. The stall speed formula is as follows:

[0155]

[0156] The minimum speed ends up being:

[0157]

[0158] Then the velocity boundary of the UAV is obtained as follows:

[0159] ;

[0160] In this embodiment, the calculated speed boundary of the UAV is as follows: Figure 3 As shown, the aerodynamic boundary shown in the figure is the calculated stall speed ;

[0161] Step 1.3: Calculate the climb angle boundary of the UAV;

[0162] From the ground to the aircraft's cruising altitude The altitude range is divided into a set number of altitude intervals. In each altitude interval, assuming that the climbing angle range remains unchanged within this altitude interval, the left boundary of the altitude interval is taken as the current climbing altitude, and the climbing angle range of the altitude interval is obtained by using a graphical method. , as the climbing angle range of the altitude interval; the climbing angle range of each altitude interval is obtained by using the graphical method The specific process is:

[0163] Assume that the UAV is climbing at the current altitude with a climbing angle Perform steady climb and obtain the following according to the dynamic equation:

[0164]

[0165]

[0166]

[0167] Where, is the pulling force of the drone, For the lift of the drone, For the resistance of the drone, is the gravity of the drone, is the climbing angle of the UAV, For the quality of the drone, is the flight speed of the drone, is the curvature radius of the UAV’s trajectory;

[0168] Combining the above formulas, we can get the climb rate for:

[0169]

[0170] Get the climb angle:

[0171]

[0172] The resistance calculation expression

[0173]

[0174] Substitute into the climb rate Evaluating the expression yields:

[0175]

[0176] Use the graphical method to solve the above equations, that is, Plot for the independent variable The function graph is within the velocity boundary of the UAV obtained in step 1.2, and the The minimum speed on the function graph of The slope of the line connecting the corresponding point and the origin is the minimum climbing angle ,like Figure 4 As shown; Considering the actual carrying capacity of the aircraft, the maximum value of the climb angle is limited to 2°, that is, ;

[0177] Then the climbing angle boundary of the UAV is obtained as follows:

[0178] .

[0179] In this embodiment, the distance from the ground to the aircraft cruising altitude is The altitude range is divided into 5 altitude intervals. In each altitude interval, the calculated climb angle boundaries of the drone are as follows:

[0180] The altitude is between 0-1500m, and the climbing angle range is 0.0533°-2°;

[0181] The altitude is between 1500-4500m, and the climbing angle range is 0.0508°-2°;

[0182] The altitude is between 4500-7500m, and the climbing angle range is 0.1619°-2°;

[0183] The altitude is between 7500-13500m, and the climbing angle range is 0.0565°-2°;

[0184] The altitude is between 13500-18000m, and the climbing angle range is 0.0391°-2°;

[0185] In this embodiment, the specific process of step 2 to establish the mathematical relationship between the drone's position coordinates, roll angle, pitch angle, yaw angle and microwave energy supply is as follows:

[0186] First, establish the coordinate transformation relationship from the navigation axis system to the body axis system; the coordinate origin of the body axis system is located at the center of gravity of the aircraft, The axis is located in the plane of symmetry of the aircraft, parallel to the axis of the fuselage, and points forward. The axis lies in the plane of symmetry of the aircraft and is perpendicular to The axis points downward. The axis is perpendicular to the symmetry plane and points to the right, satisfying the right-hand system; the navigation axis system is the ground inertial coordinate system, and the coordinate origin is the absolute coordinate (0,0,0);

[0187] Based on the positional relationship between the navigation axis system and the body axis system, the Transformation matrix for direction (roll), The transformation matrix of the direction (pitch) and The specific expression of the transformation matrix of direction (yaw) is as follows:

[0188]

[0189]

[0190]

[0191] Where, 、 、 For Transformation matrix for direction (roll), The transformation matrix of the direction (pitch) and The transformation matrix of the orientation (yaw); 、 、 They are the roll angle, pitch angle, and yaw angle of the drone at the current time step, and the roll angle at the initial moment , pitch angle , yaw angle ;

[0192] Based on the coordinates of the drone's location at the current time step and the location of the ground energy transmitting base station , obtain the normal vector of the energy irradiation surface:

[0193]

[0194] Let the initial axis matrix of the drone be:

[0195]

[0196] Then the body axis matrix after the transformation matrix is:

[0197]

[0198] drone body The plane is the receiving surface, and the normal direction of the receiving surface in the body axis system is Direction vector , after transformation, the normal vector of the receiving surface at the current time step is obtained:

[0199] ,

[0200] Where, 、 、 are the three components of the normal vector of the receiving surface at the current time step;

[0201] According to the calculation principle of plane angle in space geometry, the angle between the receiving plane and the normal vector of the irradiated surface is and The angle between them is calculated using the following formula to obtain the effective energy receiving area of ​​the UAV for the ground energy transmitting base station after considering the attitude change at the current time step. :

[0202]

[0203] Where, is the maximum energy receiving area of ​​the UAV;

[0204] Then the following formula is used to calculate the receiving efficiency of the energy transmitted by the ground energy transmitting base station at the current time step: :

[0205]

[0206] Where, is the initial output power of the ground energy transmitting base station;

[0207] Then the following formula is used to calculate the energy consumption of the UAV at the current time step:

[0208]

[0209] Where, The maximum capacity of the drone battery.

[0210] In this embodiment, step 3 specifically includes the following sub-steps:

[0211] Step 3.1: Calculate the corresponding atmospheric density based on the aircraft's altitude;

[0212] Starting from the initial moment, let time , the altitude of the drone at this time Calculate the atmospheric density corresponding to the current altitude based on the atmospheric environment model in step 1.1 ;

[0213] Step 3.2: Calculate the pulling force of the drone at the current time step , lift and resistance ;

[0214] Make the flight speed , according to the UAV motor power , calculate the pulling force of the drone at the current time step :

[0215]

[0216] Zero lift drag of the drone based on the initial parameters of the drone state , induction factor , drone gravity , UAV wing area Atmospheric density corresponding to the current altitude , flight speed , calculate the drag of the drone at the current time step :

[0217]

[0218] According to the current time of the drone's altitude , pitch angle , roll angle , based on the lift-to-drag ratio relationship of the drone, the calculated lift-to-drag ratio of the drone is , and then calculate the lift of the drone in the current time step :

[0219]

[0220] At the initial moment, the height , pitch angle , roll angle ;

[0221] Step 3.3: Based on the force on the drone, calculate the acceleration of the drone at the current time step. Specifically:

[0222] According to Newton's second law, the UAV's current time step is obtained The axial accelerations are:

[0223]

[0224]

[0225]

[0226] Where, Indicates drone Toward acceleration, Indicates drone Toward acceleration, Indicates drone Toward acceleration; is the UAV pulling force at the current time step, is the drag of the drone at the current time step, is the lift of the UAV at the current time step; For drone quality, is the weight of the drone, Represent the climb angle, yaw angle, and roll angle of the current time step respectively. The climb angle at the initial moment = , yaw angle = , roll angle = ;

[0227] If the current flight speed exceeds the speed limit of the UAV determined in step 1.2, that is, or When , the acceleration of the UAV in the current time step is regulated as follows:

[0228]

[0229]

[0230]

[0231] , , is the set acceleration control parameter; in this embodiment, , , Take 1m / s 2 ;

[0232] Step 3.4: Based on the acceleration of the drone in the current time step, calculate the yaw angle, flight speed, and position coordinates of the drone in the next time step. Specifically:

[0233] Based on the flight speed of the current time step, the yaw angle at the next moment is calculated by the following formula for:

[0234]

[0235] Where, 、 、 are the UAV’s current time step. The velocity of the direction, at the initial moment, , , ;

[0236] Assuming that the drone performs uniform acceleration in a time step, based on the acceleration and velocity of the drone in the current time step, the velocity of the drone in the next time step is calculated by the following formula:

[0237]

[0238]

[0239]

[0240] Where, is the set time step, 、 、 are the UAVs at the next time step. Speed ​​of direction;

[0241] Assuming that the UAV performs uniform acceleration in a time step, based on the acceleration and velocity of the UAV in the current time step, the displacement of the UAV in the current time step is calculated by the following formula:

[0242]

[0243]

[0244]

[0245] Where, 、 、 are the UAV’s current time step. displacement to the direction;

[0246] Then the position coordinates of the drone in the next time step are calculated by the following formula:

[0247]

[0248]

[0249]

[0250] Where, 、 、 They are the position coordinates of the drone at the current time step, and at the initial moment , , ; 、 、 are the position coordinates of the UAV in the next time step, That is, the height of the drone in the next time step;

[0251] Step 3.5: Energy consumption of the drone based on the current time step Minimum, calculate the roll angle and pitch angle of the drone in the next time step, specifically:

[0252] Based on the roll angle of the current time step and the climb angle boundary calculated in step 1.3, the optional ranges of the pitch angle and roll angle at the next time step are established as follows:

[0253] ϕ range ϵ[ϕ-5,ϕ+5]

[0254] γ range ϵ[ γ min , γ max ]

[0255]

[0256] Where, 、 、 are the roll angle, climb angle, and pitch angle of the drone at the current time step, 、 The optional range of the roll angle and climb angle for the next time step; is the angle of attack of the UAV at the current time step, when hour, ,when hour, , where is the climb angle of attack, is the cruise angle of attack;

[0257] for and , randomly in 、 50 samples were taken from each group to form 50 50, using the mathematical relationship established in step 2 to calculate the energy consumption of the drone corresponding to the 2500 combinations at the current time step Calculate and compare, select The minimum value corresponds to and As the roll and pitch angles for the next time step;

[0258] Step 3.6: Update the current time , record and store the position coordinates, attitude angle, flight speed, and energy consumption of the drone at each time step, jump to step 3.1, and repeat the above process until the set flight mission is completed; the energy consumption of the drone at each time step Perform superposition and summation to obtain the energy consumption of the entire UAV flight mission, that is, , record and store total energy consumption .

[0259] In this embodiment, Figure 6 、 Figure 7 、 Figure 8 The flight attitude angle history obtained by the method of the present invention is given. Figure 9 The flight trajectory obtained by the method of the present invention is given; Figure 10 An energy variation curve during the climb process planned based on the method of the present invention is given. To demonstrate the beneficial effects of the present invention, an energy variation curve using the steepest climb method is calculated as a comparison. The steepest climb method does not consider the influence of the UAV's attitude and only uses the maximum climb angle to climb to the cruising altitude. By comparison, it can be seen that after control planning considering the influence of attitude, the climb planned by the present invention reduces the total battery energy consumption by about 10% compared with the climb without considering the influence of attitude. This proves that the method of the present invention can effectively avoid the loss of microwave energy supply caused by attitude changes during the actual flight of the UAV, thereby effectively improving energy utilization.

[0260] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and purpose of the present invention.

Claims

1. A single microwave radiation-driven UAV flight planning method with optimal energy utilization, characterized by: The steps include: Step 1: Establish an atmospheric environment model based on the International Standard Atmosphere. For a given UAV, obtain the basic design parameters, initial state parameters, and lift-to-drag ratio relationship of the UAV. Use the aircraft performance estimation method to calculate the climb angle and flight speed boundaries of the UAV under the set flight mission. Step 2: Establish a mathematical relationship between the drone's position coordinates, roll angle, pitch angle, yaw angle, and the microwave energy supplied by a single microwave radiation source. Calculate the drone's energy consumption at the current time step based on the drone's position coordinates, roll angle, pitch angle, and yaw angle at the current time step through the mathematical relationship. The specific process of establishing the mathematical relationship between the UAV position coordinates, roll angle, pitch angle, yaw angle and the microwave energy provided by a single microwave radiation source is as follows: First, establish the coordinate transformation relationship from the navigation axis system to the body axis system; the coordinate origin of the body axis system is located at the center of gravity of the aircraft, The axis is located in the plane of symmetry of the aircraft, parallel to the axis of the fuselage, and points forward. The axis lies in the plane of symmetry of the aircraft and is perpendicular to The axis points downward. The axis is perpendicular to the symmetry plane and points to the right, satisfying the right-hand system; the navigation axis system is the ground inertial coordinate system, and the coordinate origin is the absolute coordinate (0,0,0); Based on the coordinates of the drone's location at the current time step and the location of the ground energy transmitting base station , obtain the normal vector of the energy irradiation surface: Let the initial axis matrix of the drone be: Then the body axis matrix after the transformation matrix is: 、 、 They are respectively the navigation axis system and the body axis system for The transformation matrix of the direction, The transformation matrix of the direction and the The transformation matrix of the direction; drone body The plane is the receiving surface, and the normal direction of the receiving surface in the body axis system is Direction vector , after transformation, the normal vector of the receiving surface at the current time step is obtained: ， Where, 、 、 They are the three components of the normal vector of the receiving surface at the current time step; The following formula is used to calculate the effective energy receiving area of ​​the UAV for the ground energy transmitting base station after considering the attitude change at the current time step: : Where, is the maximum energy receiving area of ​​the UAV; Then the following formula is used to calculate the receiving efficiency of the energy transmitted by the ground energy transmitting base station at the current time step: : Where, is the initial output power of the ground energy transmitting base station; Then the following formula is used to calculate the energy consumption of the UAV at the current time step: Where, The maximum capacity of the drone battery; Step 3: Establish a flight dynamics model. Based on the basic design parameters and initial state parameters of the UAV, according to the set flight mission and time step, starting from the initial state, calculate the position coordinates, yaw angle, and flight speed of the UAV in the next time step; based on the mathematical relationship established in step 2 and the minimum energy consumption of the current time step, obtain the roll angle and pitch angle of the UAV in the next time step until the flight mission is finally completed, and record and store the position coordinates, attitude angle, flight speed, energy consumption, and total energy consumption of the UAV in each time step.

2. The single microwave radiation driven UAV flight planning method with optimal energy utilization according to claim 1 is characterized by: The basic design parameters of the drone mentioned in step 1 include the gravity of the drone , the quality of the drone , UAV wing area , UAV motor power , UAV zero lift drag , the maximum lift coefficient of the UAV , the maximum capacity of drone batteries , inducing factor ; Maximum energy receiving area of ​​the drone ; Climb angle of attack , cruise angle of attack , cruising altitude ; The initial state parameters include the initial time , time step , the initial position coordinates of the drone , initial pitch angle , initial yaw angle , initial roll angle , initial climb angle , initial flight speed ,initial Directional speed ,initial Directional speed ,initial Directional speed , the initial output power of the ground energy transmitting base station , initial battery charge ;Location coordinates of ground energy transmitting base station ; The lift-to-drag ratio relationship of the UAV refers to the lift-to-drag ratio of the UAV and height , pitch angle , roll angle The mathematical form of the relationship is as follows: in It is in functional form and is determined by the aerodynamic performance of a given UAV.

3. The single microwave radiation driven UAV flight planning method with optimal energy utilization according to claim 2 is characterized in that: Step 1 specifically includes the following sub-steps: Step 1.1: Establish an atmospheric environment model based on the International Standard Atmosphere; Step 1.2: Calculate the flight speed limit of the drone; According to the two intersection points of the UAV's required power curve and available power curve, use the formula Solve and obtain the two speed values ​​corresponding to the two intersection points of the required power curve and the available power curve , respectively the minimum speed and maximum speed during level flight; is the local atmospheric density determined by the atmospheric environment model, is the flight speed of the drone, Take the intersection value of the required power curve and the available power curve; The minimum speed calculated by the above formula is equal to the stall speed Perform a second comparison and take the smaller value as the minimum speed for level flight: Then the velocity boundary of the UAV is obtained as follows: ； Step 1.3: Calculate the climb angle boundary of the UAV; From the ground to the aircraft's cruising altitude The altitude range is divided into a set number of altitude intervals. In each altitude interval, assuming that the climbing angle range remains unchanged within this altitude interval, the left boundary of the altitude interval is taken as the current climbing altitude, and the climbing angle range of the altitude interval is obtained by using a graphical method. , as the climb angle range for this altitude interval.

4. The single microwave radiation driven UAV flight planning method with optimal energy utilization according to claim 3 is characterized in that: Use the graphical method to solve the climbing angle range for each altitude interval The specific process is: Assume that the UAV is climbing at the current climbing height with a climbing angle Perform steady climb and obtain the following according to the dynamic equation: Where, is the pulling force of the drone, For the lift of the drone, For the resistance of the drone, is the gravity of the drone, is the climbing angle of the UAV, For the quality of the drone, is the flight speed of the drone, is the curvature radius of the UAV’s trajectory; Combining the above formulas, we can get the climb rate for: Get the climb angle: The resistance calculation expression Substituting into the climb rate Evaluating the expression yields: Use the graphical method to solve the above equations, that is, Plot for the independent variable The function graph is within the velocity boundary of the UAV obtained in step 1.2, and the The minimum speed on the function graph of The slope of the line connecting the corresponding point and the origin is the minimum climbing angle ; Maximum climb angle Determined according to the actual carrying capacity of the UAV.

5. The single microwave radiation driven UAV flight planning method with optimal energy utilization according to claim 1 is characterized by: Step 3 specifically includes the following sub-steps: Step 3.1: Based on the aircraft's altitude Calculate the corresponding atmospheric density ; Step 3.2: Calculate the pulling force of the drone at the current time step , lift and resistance ; Step 3.3: Based on the force acting on the drone, calculate the acceleration of the drone at the current time step; Step 3.4: Based on the acceleration of the drone in the current time step, calculate the yaw angle, flight speed, and position coordinates of the drone in the next time step; Step 3.5: Energy consumption of the drone based on the current time step Minimum, calculate the roll angle and pitch angle of the drone in the next time step; Based on the roll angle of the current time step and the climb angle boundary calculated in step 1.3, the optional ranges of the pitch angle and roll angle at the next time step are established as follows: Where, 、 is the optional range of the roll angle and climb angle for the next time step, is the set roll angle change; is the angle of attack of the UAV at the current time step, when hour, ,when hour, , where is the climb angle of attack, is the cruise angle of attack; for and , randomly in 、 Each sample is G samples, consisting of The matrix of , using the mathematical relationship established in step 2 will be The energy consumption of the UAV corresponding to the combination at the current time step Calculate and compare, select The minimum value corresponds to and As the roll and pitch angles for the next time step; Step 3.6: Update the current time , record and store the position coordinates, attitude angle, flight speed, and energy consumption of the drone at each time step, jump to step 3.1, and repeat the above process until the set flight mission is completed; the energy consumption of the drone at each time step Perform superposition and summation to obtain the energy consumption of the entire UAV flight mission , record and store total energy consumption .

6. The single microwave radiation driven UAV flight planning method with optimal energy utilization according to claim 5 is characterized by: In step 3.2, calculate the pulling force of the drone at the current time step , lift and resistance The process is: Make the flight speed , according to the UAV motor power , calculate the pulling force of the drone at the current time step : Zero lift drag of the drone based on the initial parameters of the drone state , induction factor , the gravity of the drone , UAV wing area Atmospheric density corresponding to the current altitude , flight speed , calculate the drag of the drone at the current time step : According to the current time of the drone's altitude , pitch angle , roll angle , based on the lift-to-drag ratio relationship of the drone, the calculated lift-to-drag ratio of the drone is , and then calculate the lift of the drone in the current time step : At the initial moment, the height , pitch angle , roll angle .

7. The single microwave radiation driven UAV flight planning method with optimal energy utilization according to claim 5 is characterized by: In step 3.3, the process of calculating the acceleration of the drone at the current time step based on the force acting on the drone is as follows: According to Newton's second law, the UAV's current time step is obtained The axial accelerations are: Where, Indicates drone Toward acceleration, Indicates drone Toward acceleration, Indicates drone Toward acceleration; If the current flight speed exceeds the speed limit of the UAV determined in step 1.2, the acceleration of the UAV at the current time step is regulated as follows: , , is the set acceleration control parameter.

8. The single microwave radiation driven UAV flight planning method with optimal energy utilization according to claim 5 is characterized by: In step 3.4, based on the acceleration of the drone in the current time step, the process of calculating the yaw angle, flight speed, and position coordinates of the drone in the next time step is as follows: Based on the flight speed of the current time step, the yaw angle at the next moment is calculated by the following formula for: Where, 、 、 are the UAV’s current time step. The velocity of the direction, at the initial moment, , , ; Assume that the UAV performs uniform acceleration in a time step. Based on the acceleration and velocity of the UAV in the current time step, the velocity of the UAV in the next time step can be calculated by the following formula: Where, is the set time step, 、 、 are the UAVs at the next time step. Speed ​​of direction; The displacement of the drone at the current time step is calculated by the following formula: Where, 、 、 are the UAV’s current time step. displacement to the direction; Then the position coordinates of the drone in the next time step are calculated by the following formula: Where, 、 、 They are the position coordinates of the drone at the current time step, and at the initial moment , , ; 、 、 are the position coordinates of the UAV in the next time step, As the altitude of the drone at the next time step.

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