An inverted trapezoidal wireless power transmission method supported by drones

Abstract

The present invention relates to an inverted trapezoidal wireless power transmission method supported by a drone, which belongs to the field of wireless power transmission and drone-assisted wireless communication, and comprises the following steps: S1: when wireless power transmission is performed in a blind area, the drone lowers its flight altitude and uses an inverted trapezoidal flight trajectory to charge a ground node; S2: constructing an energy consumption model of different flight postures of the drone; S3: jointly optimizing the hovering times m and the starting charging position (x B ,y B ), improve the energy receiving efficiency and fairness of the node, and ensure that the drone can return safely. The present invention adopts an inverted trapezoidal wireless power transmission method to reduce the flight altitude and transmission loss, thereby improving the energy receiving efficiency and fairness of the node while ensuring that the drone can safely reach the next base station to obtain energy replenishment.

Description

Technical Field

[0001] The present invention belongs to the field of wireless power transmission and unmanned aerial vehicle (UAV) assisted wireless communication, and relates to an inverted trapezoidal wireless power transmission method supported by a UAV. Background Art

[0002] In recent years, rotary-wing UAVs have attracted great attention in the civil and commercial fields due to their portability, flexibility, low-altitude flight and low economic cost. For example, it has been widely used by the public in natural disaster monitoring, forest fire detection, traffic management, cargo transportation and emergency search and rescue. The research on UAV-assisted wireless communications can be roughly divided into two aspects. On the one hand, UAVs can provide network coverage as aerial base stations or mobile relays to assist remote users and geographically restricted areas in the rapid deployment of wireless sensor networks. On the other hand, from the perspective of wireless power transmission, UAVs can act as mobile energy transmitters, broadcasting RF energy in the air to wirelessly power low-power nodes on the ground.

[0003] The current research work has great guiding value for the application of drones in assisting communication in wireless power transmission systems. However, in previous research work, the impact of drone flight altitude on the energy received by ground nodes was ignored. In fact, the height of the drone, that is, the distance between the drone and the node, has a great impact on the charging efficiency. The closer the drone is to the node, the more energy the node obtains. In addition, in previous research work, the fairness of node receiving energy was ignored. Therefore, we propose a drone-supported inverted trapezoidal wireless power transmission method to wirelessly charge nodes in blind areas. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide an inverted trapezoidal wireless power transmission method supported by a drone, reduce the flight altitude of the drone in the blind area, reduce the loss during wireless power transmission, and improve the energy reception efficiency and fairness of the node.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] An inverted trapezoidal wireless power transmission method supported by a drone comprises the following steps:

[0007] S1: When wireless power transmission is performed in the blind area, the drone lowers its flight altitude and uses an inverted trapezoidal flight trajectory to charge the ground node, thereby reducing the wireless power transmission distance with the ground node, thereby increasing the energy received by the ground node;

[0008] S2: Construct energy consumption models for different flight postures of drones, so that drones can safely reach the next base station for energy replenishment;

[0009] S3: Jointly optimize the number of hovering times m and the starting charging position (x B ,y B ), improve the energy reception efficiency and fairness of nodes, and ensure that the drone can return safely.

[0010] Further, in the inverted trapezoidal flight trajectory described in step S1, the flight trajectory of the drone includes seven stages: stage I: base station acceleration; stage II: uniform flight to the blind spot; stage III: descending flight to the starting charging position; stage IV: flying along the horizontal path and charging; stage V: climbing to the original height; stage VI: uniform flight out of the blind spot; stage VII: deceleration to the base station. In order to simplify the analysis and calculation, it is assumed that stage I and stage VII are a group, their acceleration / deceleration is the same and the direction is opposite; stage II and stage VI are a group, their uniform speed is the same, stage III and stage V are a group, their pitch angle is the same, and the three groups of flight stages are regarded as symmetrical structures. In the subsequent problem analysis, any stage in each group is taken for analysis, and the other stage is its symmetrical form. As a result, an inverted trapezoidal flight trajectory is eventually formed. Such a flight trajectory makes the wireless power transmission distance between the drone and the node in the blind area closer, and the wireless power transmission loss is less, so that the ground nodes can receive more energy. In stage IV, the drone will select multiple hovering points and divide the charging area into multiple areas to avoid the edge nodes receiving only less energy, which greatly improves the fairness of energy reception of ground nodes.

[0011] Furthermore, in step S2, the specific steps of constructing the energy consumption model of different flight postures are as follows:

[0012] Phase I and Phase VII: In Phase I, the UAV starts to accelerate from the base station with an acceleration of a. The acceleration time from 0 to V is The energy consumption of the drone during the acceleration phase is Assuming that the acceleration and deceleration phases are symmetrical, the energy consumption of the drone in deceleration phase VII is

[0013] Phase II and Phase VI: The UAV flies horizontally and at a constant speed to the blind spot, and its flight pitch angle τ c =0°, longitudinal air friction resistance F y =0, UAV forward flight power P V =(0,0,V), stage II and stage VI during uniform flight T V The energy consumption in V =P V T V ;

[0014] Phase III and Phase V: The drone descends to the starting charging position (x B ,y B), when the drone is pitching, the longitudinal air friction resistance is much greater than the horizontal air friction resistance, which is determined by the physical structure of the drone. Therefore, the horizontal air friction resistance is ignored and only the longitudinal air friction resistance is considered. Assuming that the pitch angle of the drone remains unchanged, when the flight total speed is set to V1 = V / cosτ c , the pitch angle is τ c , the longitudinal air friction resistance is F y- When the UAV's pitch attitude flight power is P(τ c ,F y- ,V1), UAV flight time in phase III The energy consumption in c ,F y- ,V1)=P(τ c ,F y- ,V1)T τ , H is the height of the drone at the starting point of descent; due to symmetry, the climbing time and the descending time in stage V are equal, and the energy consumption of the drone in stage V is E(τ c ,F y+ ,V1)=P(τ c ,F y+ ,V1)T τ ;

[0015] In phase IV, the drone starts to fly and charge along the horizontal path BC from the starting charging position. The specific steps are as follows:

[0016] The drone selects the starting charging position (x B ,y B ), defined as the location of the first node in the blind area that can receive the energy transmitted by the drone, i.e. The constraints are expressed as:

[0017] P uav_t +G uav_t +G gn_r -PL1≥0 (1)

[0018] Among them, P uav_t Represents the transmitting power of the UAV, G uav_t is the gain of the UAV transmitting antenna, G gn_r is the gain of the receiving antenna of the ground node, and the coordinates of point B are (x B ,y B ), the wireless power transmission loss PL1 is calculated according to the wireless power transmission loss formula, where d1 is the distance between the drone at point B and the first node,

[0019] Since any point on the path AB is within the wireless transmission radius R between the UAV and the first node, it can be selected as the starting point, that is, the charging distance of the UAV in the blind spot is BC = Δx3-2(H uav -y B ) / tanτ c In path BC, the flight path of the drone is evenly divided into multiple parts, and the flight process of each part is the same, and the distance is expressed as l m = BC / m, the acceleration of the drone is set to a2, the flight speed is V, and the flight distance when the drone accelerates or decelerates is written as Considering symmetry, the flight distance of acceleration and deceleration is l ad =2l acc , consider two situations in each charging and flight process of the drone:

[0020] Case 1: l m >l ad ; In each part, the drone has four flight postures: uniform flight, deceleration, hovering and acceleration. The flight distance of the drone at speed V is l c =(l m -l ad ) and charging time is The flight energy consumption of the drone in the uniform speed stage is E c =P V T c ; The energy consumption of UAV flight operation in each part is expressed as

[0021] E uav =E acc +E dec +E hover +E c (2)

[0022] The time required for acceleration and deceleration operation The time during the hovering will be described in detail later.

[0023] Case 2: l m ≤l ad ; In each part, the drone has only three flight attitudes: acceleration, deceleration and hovering; because the given parameters cannot keep the drone at a shorter a2 or V distance, or during the acceleration and deceleration phases of the given parameters, the drone’s distance cannot be less than l ad Therefore, in order to meet the distance condition, the a2 or V of the drone is changed:

[0024]

[0025] When a2 is constant, the acceleration and deceleration time of the drone When V is constant, the time of the UAV in the acceleration and deceleration stages is the same as in Case 1, and the flight energy consumption of each part of the UAV is:

[0026] E uav =E acc +E dec +E hover (4)

[0027] In the horizontal path BC, the energy available for UAV flight and charging is expressed as:

[0028]

[0029] Further, the specific steps of step S3 are as follows:

[0030] During the charging process in the blind area, the drone not only needs to charge the node at the hovering point, but also needs additional energy to maintain the hovering attitude. Therefore, the hovering time T h It is expressed as:

[0031]

[0032] Among them, T fly It is the sum of the acceleration, deceleration and uniform flight time of the drone;

[0033] The drone can charge the node during the BC flight. Four typical flight postures are considered: the hovering point is located at the center of each small segment, the left and right sides are deceleration and acceleration, and both sides are constant speed during the flight; each small part is discretized into j parts according to the distance, and each part is X mj (0≤j≤J), the starting point of each segment is the end point of the previous segment:

[0034] X mJ =X (m-1)0 (7)

[0035] Determine the flight attitude interval of each discrete point. The charging time for different intervals is different:

[0036] 1) Charging time during the drone's constant speed flight J1 is the number of discrete points;

[0037] 2) Charging time during the acceleration or deceleration of the drone J2 is the number of discrete points;

[0038] 3) During the drone hovering period, the charging time is T h ;

[0039] In each section, when the drone charges the node while decelerating, accelerating, and flying at a constant speed, the straight-line distance between the drone and the node changes continuously, and the RF energy received by the kth node is calculated as:

[0040]

[0041] Where Ψ=P uav_t +G uav_t +G gn_r -20log 10 (f)+165.33dB, And B -H gn ≥1m;

[0042] The energy received by the kth node in the blind area in the m1 interval is expressed as:

[0043]

[0044] Where, J = J1 + J2 + J3 + J4, η is the constant conversion efficiency of RF to DC, and They represent the RF energy received by the nodes in the blind area during the flight and hovering of the UAV, respectively;

[0045] In the entire BC horizontal flight path, the DC energy received by the kth node is expressed as:

[0046]

[0047] In the inverted trapezoidal wireless power transmission method, the total DC energy that can be received by the nodes in the blind area is expressed as:

[0048]

[0049] In order to improve the energy receiving efficiency and fairness of the nodes, it is necessary to optimize the number of hovering times of the drone and the coordinates of the starting position B. The constraints ensure that the drone can safely reach the next base station to charge after charging the node in the blind area. Therefore, the optimization problem is expressed as follows:

[0050] (m,x B ,y B )=argmax(E r ) (12)

[0051] The constraints are:

[0052] E uav ≤E available (13)

[0053] The above optimization problem is solved by intelligent algorithm to obtain the optimal hovering times and starting hovering position of the UAV in the blind spot.

[0054] The beneficial effect of the present invention is that when a network blind spot is formed in a wireless sensor network because some nodes lack energy and cannot send data, the drone can be used as a mobile energy transmitter to wirelessly supply energy to the nodes, so that the network can return to normal working state. While ensuring that the drone can safely reach the next base station to obtain energy replenishment, the present invention adopts an inverted trapezoidal wireless power transmission method to reduce the flight altitude and transmission loss, thereby improving the energy reception efficiency and fairness of the nodes.

[0055] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0057] Figure 1 is a model diagram of an inverted trapezoidal wireless power transmission system supported by the drone of the present invention;

[0058] Figure 2 is a schematic diagram of the process of the inverted trapezoidal wireless power transmission method;

[0059] Figure 3 It is a schematic diagram of the starting position of point B in the wireless power transmission method. DETAILED DESCRIPTION

[0060] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0061] Among them, the drawings are only used for illustrative explanations, and they only represent schematic diagrams rather than actual pictures, and should not be understood as limitations on the present invention. In order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0062] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "rear", etc. indicate the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0063] This embodiment is based on an inverted trapezoidal wireless power transmission system supported by a drone. Figure 1 As shown, it is assumed that the specifications of the ground nodes are the same, and the system's wireless power transmission area for nodes is a one-dimensional node area with consistent spacing between base stations. After the base station is loaded with energy, the drone undergoes a series of flight operations, including acceleration, constant speed, and descent altitude to reach the network blind area to charge the nodes in this area. After charging is completed, it climbs, maintains a constant speed, and decelerates to reach the next base station for energy loading. In an actual wireless sensor network, some nodes between base stations cannot obtain enough energy from the base station to transmit data back because their deployment locations are far away from the base station. Therefore, long-term work has caused k nodes in the wireless sensor network to form a network blind area. In view of the fact that some data is missing due to insufficient energy at the nodes, the drone is implemented to wirelessly supply energy to some nodes, including the following steps;

[0064] like Figure 2 As shown in the figure, an inverted trapezoidal flight trajectory is used to charge the ground node. The flight trajectory of the drone is mainly divided into seven stages: accelerating from the base station, flying to the blind spot at a constant speed, descending to the starting charging position, flying along a horizontal path and charging, climbing to the original height, flying out of the blind spot at a constant speed, and then decelerating to the base station. They are respectively recorded as I to VII.

[0065] Phase I and Phase VII: In Phase I, the drone starts to accelerate from the base station. Assuming the acceleration is set to a, the acceleration time of the drone from 0 to V is a>0. Therefore, the energy consumption of the UAV during the acceleration phase is To simplify the analysis, it is assumed that the acceleration and deceleration phases are symmetrical. Therefore, the energy consumption of the drone in deceleration phase VII is

[0066] Phase II and Phase VI: The UAV flies horizontally and at a constant speed to the blind spot, and its flight pitch angle τ c =0°, longitudinal air friction resistance F y = 0. Therefore, the forward flight power of the drone is P V =(0,0,V). So stage II and stage VI are in the uniform flight period T V The energy consumption in V =P V T V .

[0067] Phase III and Phase V: The drone descends to the starting charging position (x B ,y B ). When the drone is pitching, the longitudinal air friction resistance is much greater than the horizontal air friction resistance, which is determined by the physical structure of the drone. Therefore, we ignore the horizontal air friction resistance and only consider the longitudinal air friction resistance. Assume that the pitch angle of the drone remains unchanged. When the total flight speed is set to V1 = V / cosτ c , the pitch angle is τ c , the longitudinal air friction resistance is F y- When the UAV's pitch attitude flight power is P(τ c ,F y- ,V1). Therefore, the UAV’s flight time in phase III is The energy consumption in c ,F y- ,V1)=P(τ c ,F y- ,V1)T τ , H is the height of the drone at the starting point of descent. Due to symmetry, the climbing time and the descending time in stage V are equal, so the energy consumption of the drone in stage V is E(τ c ,F y+ ,V1)=P(τ c ,F y+ ,V1)T τ .

[0068] In phase IV, the drone starts to fly and charge along the horizontal path BC from the starting charging position. The specific steps are as follows:

[0069] like Figure 2 As shown in Figure 2, when the UAV charges the nodes in the blind area, it needs to select the starting charging position B, which is defined as the position where the first node can receive the energy transmitted by the UAV, that is, The constraints can be expressed as:

[0070] Puav_t +G uav_t +G gn_r -PL1≥0 (1)

[0071] Among them, P uav_t Represents the fixed transmission power of the UAV, G uav_t is the gain of the UAV transmitting antenna, G gn_r is the receiving antenna gain of the ground sensor node. Assume that the coordinates of point B are (x B ,y B ), the wireless power transmission loss PL1 can be calculated according to the wireless power transmission loss formula, where d1 is the distance between the drone at point B and the first node,

[0072] like Figure 3 As shown in the figure, as long as the point on AB is within the wireless transmission radius R between the drone and the first node, it can be selected as the starting point, that is, the charging distance of the drone in the blind area is BC = Δx3-2(H uav -y B ) / tanτ c , assuming that in BC, the flight path of the drone is evenly divided into m parts, and the flight process of each part is the same, and the distance is expressed as l m = BC / m, the acceleration of the drone is set to a2, and the flight speed is V. Under these conditions, the flight distance of the drone when accelerating or decelerating is written as Considering symmetry, the flight distance of acceleration and deceleration is l ad =2l acc ,There are two situations to be discussed in each part of the UAV flight and charging process.

[0073] Case 1: l m >l ad In each part, the drone has four flight postures: uniform flight, deceleration, hovering and acceleration. Under the above parameters, the flight distance of the drone at speed V is l c =(l m -l ad ) and charging time is Therefore, the flight energy consumption of the UAV in the uniform speed stage is E c =P V T c , then, the energy consumption of the UAV flight operation in each part can be expressed as

[0074] E uav =E acc +E dec +E hover +E c (2)

[0075] The time required for acceleration and deceleration operation The time during the hovering will be described in detail later.

[0076] Case 2: l m ≤l ad In each part, the drone has only three flight attitudes: acceleration, deceleration and hovering. Since the given parameters cannot keep the drone at a shorter a2 or V distance, or the drone’s distance cannot be less than l during the acceleration and deceleration phases of the given parameters, ad Therefore, in order to meet the conditions, the drone's a2 or V needs to be changed.

[0077]

[0078] When a2 is constant, the acceleration and deceleration time of the drone When V is constant, the time spent by the drone in the acceleration and deceleration phases is the same as in Case 1. Therefore, the flight energy consumption of each part of the drone is

[0079] E uav =E acc +E dec +E hover (4)

[0080] like Figure 2 As shown, in the horizontal path BC, the energy available for UAV flight and charging can be expressed as

[0081]

[0082] Where E load is the energy loaded by the drone at the base station, is the energy consumed by the drone to maintain hovering during loading. is the energy consumed by acceleration and deceleration outside the blind zone, E V is the energy consumed in the uniform flight phase outside the blind zone, E down and E climb They respectively represent the energy consumed when the UAV descends to enter the blind spot and climbs to leave the blind spot.

[0083] The drone not only needs to charge the node at the hovering point, but also needs additional energy to maintain the hovering attitude. Therefore, the hovering time T h It can be expressed as

[0084]

[0085] Among them, T fly It is the sum of the acceleration, deceleration and uniform flight time of the drone.

[0086] The drone can charge the node during the BC flight. Consider four typical flight postures: the hovering point is located at the center of each segment, the left and right sides are deceleration and acceleration, and then both sides are at a constant speed during flight. Discretize each segment into j parts according to the distance, each part is X mj (0≤j≤J), the starting point of each segment is the end point of the previous segment.

[0087] X mJ =X (m-1)0 (7)

[0088] Determine the flight attitude of each discrete point, and the charging time at different intervals is different

[0089] 1) Charging time during the drone's constant speed flight J1 is the number of discrete points.

[0090] 2) Charging time during the acceleration or deceleration of the drone J2 is the number of discrete points.

[0091] 3) During the drone hovering period, the charging time is T h .

[0092] In each section, the straight-line distance between the drone and the node changes continuously as the drone charges the node while decelerating, accelerating, and flying at a constant speed. Therefore, the RF energy received by the kth node can be calculated as

[0093]

[0094] Where Ψ=P uav_t +G uav_t +G gn_r -20log 10 (f) +165.33dB, distance between drone and node And B -H gn ≥1m.

[0095] The energy received by the kth node in the blind area in the m1 interval can be expressed as

[0096]

[0097] Where, J = J1 + J2 + J3 + J4, η is the constant conversion efficiency of RF to DC, and They represent the RF energy received by the nodes in the blind area during the flight and hovering of the UAV, respectively.

[0098] In the entire BC horizontal flight path, the DC energy received by the kth node can be expressed as

[0099]

[0100] In the inverted trapezoidal wireless power transmission method, the total DC energy that the nodes in the blind area can receive can be expressed as

[0101]

[0102] In order to improve the energy receiving efficiency and fairness of the nodes, it is necessary to optimize the coordinates of the starting position B of the drone and the number of hovering times. The constraints ensure that the drone can safely reach the next base station to charge after charging the node in the blind area. Therefore, we formulate the optimization problem as follows

[0103] (m,x B ,y B )=argmax(E r ) (12)

[0104] The constraints are:

[0105] E uav ≤E available (13)

[0106] By solving the above optimization problem through intelligent algorithms, the optimal hovering times and starting hovering position of the drone in the blind spot can be obtained.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. An inverted trapezoidal wireless power transmission method supported by a drone, characterized in that: The following steps are involved: S1: When wireless power transmission is performed in the blind area, the UAV lowers its flight altitude and uses an inverted trapezoidal flight trajectory to charge the ground node; in the inverted trapezoidal flight trajectory, the UAV's flight trajectory includes seven stages: Stage I: Base station acceleration; Phase II: Fly to the blind spot at a constant speed; Phase III: Descending flight to the starting charging position; Stage IV: flying along a horizontal path and charging; Stage V: climbing to the original altitude; Stage VI: flying out of the blind spot at a constant speed; Stage VII: decelerating to the base station; Stage I and Stage VII are a group, their acceleration / deceleration is the same and the direction is opposite; Stage II and Stage VI are a group, their speed is the same when they are at a constant speed, Stage III and Stage V are a group, their pitch angle is the same, and the three groups of flight stages are considered to be a symmetrical structure; S2: Construct energy consumption model of different flight postures of UAV; S3: Jointly optimize the number of hovering times m and the starting charging position (x B ,y B ), improve the energy reception efficiency and fairness of nodes, and ensure that the drone can return safely.

2. The inverted trapezoidal wireless power transmission method supported by a drone according to claim 1, characterized in that: In step S2, the specific steps of constructing the energy consumption model of different flight postures are as follows: Phase I and Phase VII: In Phase I, the UAV starts to accelerate from the base station with an acceleration of a. The acceleration time from 0 to V is The energy consumption of the drone during the acceleration phase is Assuming that the acceleration and deceleration phases are symmetrical, the energy consumption of the drone in deceleration phase VII is Phase II and Phase VI: The UAV flies horizontally and at a constant speed to the blind spot, and its flight pitch angle τ c =0°, longitudinal air friction resistance F y =0, UAV forward flight power P V =(0,0,V), stage II and stage VI during uniform flight T V The energy consumption in V =P V T V ; Phase III and Phase V: The drone descends to the starting charging position B (x B ,y B ), when the UAV is pitching, only the longitudinal air friction resistance is considered. Assuming that the pitch angle of the UAV remains unchanged, when the flight total speed is set to V1 = V / cosτ c , the pitch angle is τ c , the longitudinal air friction resistance is F y- When the flight power of the UAV pitch attitude is P(τ c ,F y- ,V1), UAV flight time in phase III The energy consumption in c ,F y- ,V1)=P(τ c ,F y- ,V1)T τ , H is the height of the drone at the starting point of descent; due to symmetry, the climbing time and the descending time in stage V are equal, and the energy consumption of the drone in stage V is E(τ c ,F y+ ,V1)=P(τ c ,F y+ ,V1)T τ ; Phase IV: The drone starts to fly and charge along the horizontal path BC from the starting charging position B. The specific steps are as follows: The drone selects the starting charging position B(x B ,y B ), defined as the location of the first node in the blind area that can receive the energy transmitted by the drone, i.e. The constraints are expressed as: P uav_t +G uav_t +G gn_r -PL1≥0 (1) Among them, P uav_t Represents the transmitting power of the UAV, G uav_t is the gain of the UAV transmitting antenna, G gn_r is the gain of the receiving antenna of the ground node, and the coordinates of point B are (x B ,y B ), the wireless power transmission loss PL1 is calculated according to the wireless power transmission loss formula, where d1 is the distance between the drone at point B and the first node, The charging distance of the drone in the blind area is BC = Δx3-2(H uav -y B ) / tanτ c In path BC, the flight path of the drone is evenly divided into multiple parts, and the flight process of each part is the same, and the distance is expressed as l m = BC / m, the acceleration of the drone is set to a2, the flight speed is V, and the flight distance when the drone accelerates or decelerates is written as Considering symmetry, the flight distance of acceleration and deceleration is l ad =2l acc , consider two situations in each charging and flight process of the drone: Case 1: l m >l ad ; In each part, the drone has four flight postures: uniform flight, deceleration, hovering and acceleration. The flight distance of the drone at speed V is l c =(l m -l ad ) and charging time is The flight energy consumption of the drone in the uniform speed stage is E c =P V T c ; The energy consumption of UAV flight operation in each part is expressed as AND uav =And acc +E dec +E hover +E c (2) The time required for acceleration and deceleration operation The time during the hover will be described in detail later; Case 2: l m ≤l ad ; In each part, the drone has only three flight attitudes: acceleration, deceleration and hovering; Change the drone's a2 or V: When a2 is constant, the acceleration and deceleration time of the drone When V is constant, the time of the UAV in the acceleration and deceleration stages is the same as in Case 1, and the flight energy consumption of each part of the UAV is: AND uav =And acc +E dec +E hover (4) In the horizontal path BC, the energy available for UAV flight and charging is expressed as:

3. The inverted trapezoidal wireless power transmission method supported by a drone according to claim 1, characterized in that: The specific steps of step S3 are as follows: The time during the hovering period T h It is expressed as: Among them, T fly It is the sum of the acceleration, deceleration and uniform flight time of the drone; The drone can charge the node during BC flight. Four typical flight postures are considered: the hovering point is located at the center of each small segment, the left and right sides are deceleration and acceleration, and both sides are constant speed during flight; each small segment is discretized into J parts according to the distance, and each part is X mj (0≤j≤J), the starting point of each segment is the end point of the previous segment: Determine the flight attitude interval of each discrete point. The charging time for different intervals is different: 1) Charging time during the drone's constant speed flight J1 is the number of discrete points; 2) Charging time during the acceleration or deceleration of the drone J2 is the number of discrete points; 3) During the drone hovering period, the charging time is T h ; In each section, when the drone charges the node while decelerating, accelerating, and flying at a constant speed, the straight-line distance between the drone and the node changes continuously, and the RF energy received by the kth node is calculated as: Where Ψ=P uav_t +G uav_t +G gn_r -20log 10 (f)+165.33dB, And B -H gn ≥1m; The energy received by the kth node in the blind area in the m1 interval is expressed as: Where, J = J1 + J2 + J3 + J4, η is the constant conversion efficiency of RF to DC, and They represent the RF energy received by the nodes in the blind area during the flight and hovering of the UAV, respectively; In the entire BC horizontal flight path, the DC energy received by the kth node is expressed as: In the inverted trapezoidal wireless power transmission method, the total DC energy that can be received by the nodes in the blind area is expressed as: The optimization problem is formulated as follows: (m,x B ,y B )=argmax(E r ) (12) The constraints are: AND uav ≤E available (13) The above optimization problem is solved by intelligent algorithm to obtain the optimal hovering times and starting hovering position of the UAV in the blind spot.

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