Unmanned aerial vehicle power supply management system

Abstract

The invention discloses an unmanned aerial vehicle power supply management system, belongs to the technical field of unmanned aerial vehicle power supply management, and solves the problem that no power supply management for cooperation of a whole unmanned aerial vehicle cluster is provided to improve power supply utilization. Comprising a flight monitoring module, an endurance monitoring module, a track comparison module and a flight control module, the flight monitoring module, the endurance monitoring module and the track comparison module are all in communication connection with the flight control module, and the flight monitoring module and the endurance monitoring module are also in communication connection with the track comparison module. The flight monitoring module is used for collecting flight parameters of each unmanned aerial vehicle in the unmanned aerial vehicle cluster and flight formation of the unmanned aerial vehicle cluster and feeding back to the flight control module, and the endurance monitoring module is used for collecting endurance information of each unmanned aerial vehicle in the unmanned aerial vehicle cluster and feeding back to the flight control module. The leader unmanned aerial vehicle and the communication unmanned aerial vehicle are replaced regularly, so that all the unmanned aerial vehicles share energy consumption, cluster influence caused by insufficient electric energy of a single unmanned aerial vehicle is avoided, power management is optimized, and cluster flight time of the unmanned aerial vehicles is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle power management, and in particular to an unmanned aerial vehicle power management system. Background Art

[0002] Drones, also known as unmanned aerial vehicles (UAVs), are aircraft that can be remotely controlled or fly autonomously without a human pilot. They are widely used in military reconnaissance, aerial photography, agricultural monitoring, logistics and distribution, and many other fields. With its flexibility and cost-effectiveness, drone technology is constantly innovating modern operations.

[0003] At present, with the increase in demand, the work of a single drone has evolved into a drone cluster, which is a collaborative system composed of multiple drones that can jointly perform complex tasks, such as flight performances, express logistics, precision agriculture, urban transportation, military reconnaissance, aerial photography, agricultural monitoring, logistics distribution, etc. Drone clusters achieve self-organization, collaboration, stability and environmental adaptability by simulating the intelligent behavior of biological groups in nature, such as pigeons avoiding obstacles and geese forming formations. This cluster system is not just a simple superposition of single drones, but a synergistic effect is generated through the cluster's autonomous control strategy to achieve group intelligence and achieve the effect of "1+1>2".

[0004] Since drones and even drone clusters need to cooperate with the above strategies to carry out various tasks, their power management becomes a more important part. Drone power management is a key technology to ensure the stable operation of drones. It involves power conversion, power distribution, detection and power management. The drone power management system plays a core role in drones. It is mainly responsible for providing stable and reliable power for various components of drones, reducing system power consumption and extending battery life. In addition, the integrated characteristics of drone power management systems help save space, achieve product miniaturization, reduce costs, and improve the uniformity and orderliness of system power supply. Through efficient power management, drones can maintain performance under various environmental conditions, while optimizing energy use to ensure flight safety and the smooth completion of missions.

[0005] However, the current UAV power management system is mainly for the power management of a single UAV during flight. When the UAV is used in a UAV cluster, the UAV cluster is a whole, and it is necessary to adjust the power utilization of each UAV according to the cooperation of the UAV cluster. Therefore, a UAV management system is needed that can perform collaborative power management for the entire UAV cluster to improve power utilization.

[0006] Therefore, a UAV power management system is proposed to solve or alleviate the above problems. Summary of the invention

[0007] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a power management system for unmanned aerial vehicles.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] A power management system for unmanned aerial vehicles comprises a flight monitoring module, a battery life monitoring module, a trajectory comparison module, and a flight control module. The flight monitoring module, the battery life monitoring module, and the trajectory comparison module are all connected to the flight control module in communication. The flight monitoring module and the battery life monitoring module are also connected to the trajectory comparison module in communication. The flight monitoring module is used to collect flight parameters of each unmanned aerial vehicle in a unmanned aerial vehicle cluster and the flight formation of the unmanned aerial vehicle cluster and feed them back to the flight control module. The battery life monitoring module is used to collect battery life information of each unmanned aerial vehicle in the unmanned aerial vehicle cluster and feed it back to the flight control module. The trajectory comparison module is used to judge the current flight trajectory process, formulate an adjusted flight trajectory, and feed it back to the flight control module. The flight control module is used to determine whether to replace the original leader unmanned aerial vehicle with the remaining unmanned aerial vehicles in the unmanned aerial vehicle cluster according to the battery life information of the unmanned aerial vehicles in the unmanned aerial vehicle cluster before each flight trajectory adjustment, and the best choice for replacing the original leader unmanned aerial vehicle.

[0010] Preferably, the flight monitoring module is used to collect the flight parameters of each drone in the drone cluster and the flight formation of the drone cluster and feed them back to the flight control module, including the following steps:

[0011] A drone cluster is defined as a leader drone, a communication drone, and several common drones, wherein the leader drone is connected to the common drones through the communication drone;

[0012] The flight parameters are defined as leader parameters, team member parameters, and environmental parameters. The leader parameters include the flight speed V of the leader drone. lead , the team member parameters include the flight speed V of the ordinary drone f , drag coefficient C Df , Load weight W f , and acceleration A f , the environmental parameters include wind speed V wind , wind direction, and air density ρ;

[0013] Collect the real-time flight parameters of the leader drone and other ordinary drones and feed them back to the flight control module.

[0014] Preferably, the flight monitoring module is used to collect the flight parameters of each drone in the drone cluster and the flight formation of the drone cluster and feed them back to the flight control module, and also includes the following steps:

[0015] The leader drone generates a flight formation and shares it with several ordinary drones via the communication drone;

[0016] The leader drone is used as the origin to establish spatial coordinates in combination with the flight formation, and the communication drone and several ordinary drones are used to generate the coordinate points (x, y, z) of each drone;

[0017] Calculate the distance between each ordinary drone and the leader drone and feed it back to the flight control module.

[0018] Calculate the distance between each ordinary drone and the communication drone and feed it back to the flight control module.

[0019] Preferably, the endurance monitoring module is used to collect the endurance information of each drone in the drone cluster and feed it back to the flight control module, including the following steps:

[0020] Collect the current remaining power of each drone [E lead ,E com ,E1,E2,…,E n ];

[0021] Calculate the average remaining power

[0022] The current remaining power of each drone and the average remaining power E avg Feedback to the flight control module.

[0023] Preferably, the trajectory comparison module is used to determine the current flight trajectory process, formulate the adjusted flight trajectory and feed back to the flight control module, including the following steps:

[0024] The leader drone conducts environmental monitoring, provides leader parameters, and locates its own coordinates and the destination coordinates through GPS;

[0025] The leader drone uses the particle swarm optimization algorithm to optimize and adjust the flight trajectory and determine the subsequent flight trajectory;

[0026] Every 5-10 minutes, the leader drone's own coordinate position is used to determine whether 90% of the subsequent flight trajectory has been completed. If completed, the subsequent steps are carried out and a nearly completed signal is output to the flight control module. If not completed, the flight continues;

[0027] Repeat the above steps.

[0028] Preferably, the flight control module is used to determine whether to replace the original leader drone with the remaining drones in the drone cluster and the best choice for replacing the original leader drone according to the endurance information of the drones in the drone cluster before each flight trajectory adjustment, including the following steps:

[0029] Receive the signal from the drone that is about to be completed, and calculate the remaining power of each drone according to its current remaining power and the average remaining power E avg Determine whether the remaining battery power of the leader drone is less than the average remaining battery power E avg , if the remaining battery power of the leader drone is greater than the average remaining battery power E avg , the original leader drone is maintained. If the remaining battery power of the leader drone is less than the average remaining battery power E avg , then select an ordinary drone to replace the original leader drone;

[0030] The power consumption E required for each ordinary drone to replace the original leader drone is calculated through the leader parameters, team member parameters, and environmental parameters. c ;

[0031] Combined with the power consumption of each ordinary drone to replace the original leader drone E c The remaining power of each ordinary drone [E lead ,E com ,E1,E2,…,E n ], and get the remaining power of each ordinary drone after the replacement [E 1-c ,E 2-c ,…,E n-c ];

[0032] After the swap, the remaining power of each common drone [E 1-c ,E 2-c ,…,E n-c ] are sorted in descending order, and the first ranked ordinary drone is selected to replace the leader drone, and the leader drone replaces the ordinary drone.

[0033] Preferably, the power consumption E required for each ordinary drone to replace the original leader drone is calculated by using the leader parameters, team member parameters, and environmental parameters. c , including the following steps,

[0034] Combine wind speed and relative position between ordinary drone and leader drone to correct the actual flight speed V of ordinary drone e , V e =V e +V wind ×cos(θ), where θ is the angle between wind direction and flight direction;

[0035] Simulate the flight time t of each ordinary drone flying to the original leader drone position f ,

[0036] Calculate the lift L of the ordinary drone flying to the original leader drone’s position, L = W f ;

[0037] Calculate the drag of a normal drone flying to the original leader drone's position Where S is the total surface area of ​​the UAV;

[0038] Calculate the power E required for each ordinary drone to replace the original leader drone c ,

[0039] The remaining power of each common drone [E lead ,E com ,E1,E2,…,E n ] minus the power consumption E required for each ordinary drone to replace the original leader drone c , and obtain the remaining power of each ordinary drone after the replacement [E 1-c ,E 2-c ,…,E n-c ].

[0040] Preferably, it also includes a communication module, which is communicatively connected to the flight monitoring module, the endurance monitoring module, the trajectory comparison module, and the flight control module. The communication module is used for signal transmission, collecting the signal strength of each ordinary drone, and determining whether there is a position with a better signal than the original communication drone based on the drone endurance information, the flight parameters of each drone, and the flight formation of the drone cluster before each flight trajectory adjustment, and switching the corresponding ordinary drone to the current communication drone.

[0041] Preferably, the communication module is used for signal transmission, collecting the signal strength of each ordinary drone, and determining whether there is a position with a better signal than the original communication drone according to the drone endurance information, the flight parameters of each drone, and the flight formation of the drone cluster before each flight trajectory adjustment, and switching the corresponding ordinary drone to the current communication drone, including the following steps:

[0042] Extract the distance D between the leader drone and the communication drone;

[0043] Extract the distance D between the ordinary drone and the communication drone w ;

[0044] Calculate the signal strength from the leader drone to the communication drone Calculate the signal strength from the communication drone to each regular drone Where K is a constant;

[0045] A comprehensive signal quality index Q is set to evaluate the effect of communication drones at different locations.

[0046] Traverse the position of each ordinary drone, use it as the position of the communication drone and calculate to find the drone coordinates at the maximum comprehensive signal quality index Q;

[0047] Determine whether the coordinates of the drone at the maximum comprehensive signal quality index Q are consistent with the coordinates of the original communication drone. If they are consistent, maintain the original state. If they are inconsistent, switch the ordinary drone at the coordinates of the drone at the maximum comprehensive signal quality index Q to the current communication drone.

[0048] The present invention has the following beneficial effects:

[0049] The present invention can replace the drones that serve as the leader drone and the communication drone at intervals during the flight of the drone cluster, thereby ensuring that the two positions of the leader drone and the communication drone, which consume the most power, can be shared by all the drones. In this way, it can also avoid the situation where the power of a certain drone in the drone cluster becomes a shortcoming and affects the normal flight of the entire drone cluster. The power management system reduces the power consumption burden of each drone, and reasonably allocates the energy of each drone in the entire drone cluster, so that the entire drone cluster can operate for a longer working time. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 It is a structural block diagram of the present invention.

[0052] 1. Flight monitoring module; 2. Endurance monitoring module; 3. Trajectory comparison module; 4. Flight control module; 5. Communication module. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0054] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0056] In the description of the present invention, it should be understood that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or are the orientations or positional relationships in which the product of the invention is conventionally placed when in use, or are the orientations or positional relationships conventionally understood by those skilled in the art. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0057] Furthermore, the terms “first”, “second”, “third”, etc. are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.

[0058] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0059] A UAV power management system, such as Figure 1As shown, it includes a flight monitoring module 1, a battery life monitoring module 2, a trajectory comparison module 3, and a flight control module 4. The flight monitoring module 1, the battery life monitoring module 2, and the trajectory comparison module 3 are all connected to the flight control module 4 in communication. The flight monitoring module 1 and the battery life monitoring module 2 are also connected to the trajectory comparison module in communication. The flight monitoring module 1 is used to collect the flight parameters of each drone in the drone cluster, as well as the flight formation of the drone cluster and feed them back to the flight control module 4. The battery life monitoring module 2 is used to collect the battery life information of each drone in the drone cluster and feed it back to the flight control module 4. The trajectory comparison module 3 is used to determine the current flight trajectory process, formulate the adjusted flight trajectory and feed it back to the flight control module 4. The flight control module 4 is used to determine whether to replace the original leader drone with the remaining drones in the drone cluster according to the battery life information of the drones in the drone cluster before each flight trajectory adjustment, and the best choice for replacing the original leader drone.

[0060] The power management system provides real-time data of each drone in the drone cluster through the flight monitoring module 1 and the endurance monitoring module 2, such as the flight parameters of each drone in the drone cluster, the flight formation of the drone cluster, and the endurance information of each drone in the drone cluster. These data are used in the trajectory comparison module 3 to assist the drone cluster in optimizing its flight route. At the same time, before each optimization, the flight control module 4 can also judge whether to replace the original leader drone with the remaining drones in the drone cluster based on these data, and select ordinary drones with sufficient power and less power consumption when switched to the position of the leader drone to replace the original leader drone, so as to make reasonable choices for the power management allocation of the entire drone cluster. In this way, when the drone cluster performs tasks, the leader and communication roles of the drones are regularly replaced to balance the energy consumption of each drone. This strategy prevents a single drone from affecting the flight of the entire cluster due to insufficient power. The power management system therefore reduces the energy consumption of each drone and achieves balanced energy distribution, so that the entire cluster can continue to work for a longer time.

[0061] Preferably, the flight monitoring module 1 is used to collect the flight parameters of each drone in the drone cluster and the flight formation of the drone cluster and feed them back to the flight control module 4, including the following steps:

[0062] The drone cluster is defined as a leader drone, a communication drone, and several ordinary drones. The leader drone communicates with several ordinary drones through the communication drone.

[0063] The flight parameters are defined as leader parameters, team member parameters, and environmental parameters. The leader parameters include the flight speed V of the leader drone. lead , the team member parameters include the flight speed V of ordinary drones f , drag coefficient C Df, Load weight W f , and acceleration A f , environmental parameters include wind speed V wind , wind direction, and air density ρ;

[0064] The real-time flight parameters of the leader UAV and other common UAVs are collected and fed back to the flight control module 4 .

[0065] The flight monitoring module 1 defines each drone in the drone cluster, and arranges their respective clear work functions according to the definition. It can also provide feedback to the flight control module 4 on the real-time flight parameters of the leader drone, communication drone, and ordinary drones, thereby ensuring that the subsequent modules can provide these data in a timely manner when they need to use them, thereby speeding up the efficiency of calculations and reducing power consumption.

[0066] Preferably, the flight monitoring module 1 is used to collect the flight parameters of each drone in the drone cluster and the flight formation of the drone cluster and feed them back to the flight control module 4, and also includes the following steps:

[0067] The leader drone generates a flight formation and shares it with several ordinary drones via the communication drone;

[0068] The leader drone is used as the origin to establish spatial coordinates in combination with the flight formation, and the communication drone and several ordinary drones are used to generate the coordinate points (x, y, z) of each drone;

[0069] Calculate the distance between each common drone and the leader drone and feed it back to the flight control module 4.

[0070] Calculate the distance between each common UAV and the communication UAV and feed it back to the flight control module 4.

[0071] Through the above method, the distance between each ordinary UAV and the leader UAV, and the distance between each ordinary UAV and the communication UAV can be transmitted to the flight control module 4. The distance between each ordinary UAV and the leader UAV, and the distance between each ordinary UAV and the communication UAV can be calculated in advance, which can reduce the time and energy required for subsequent calculations of the flight control module 4. At the same time, spatial coordinates can be established to help understand the position of each UAV in the UAV cluster, so as to serve as a reference when adjusting the UAV position later.

[0072] Preferably, the endurance monitoring module 2 is used to collect the endurance information of each drone in the drone cluster and feed it back to the flight control module 4, including the following steps:

[0073] Collect the current remaining power of each drone [Elead ,E com ,E1,E2,…,E n ];

[0074] Calculate the average remaining power

[0075] The current remaining power of each drone and the average remaining power E avg Feedback to flight control module 4.

[0076] The endurance monitoring module 2 is used to perform real-time statistics on the current remaining power of each drone, and calculate the average remaining power in advance, so that the subsequent flight control module 4 can directly extract the above data when it needs to use it, without having to perform excessive calculations, thereby reducing the operating burden of the flight control module 4 and its power consumption.

[0077] Preferably, the trajectory comparison module 3 is used to determine the current flight trajectory process, formulate the adjusted flight trajectory and feed back to the flight control module 4, including the following steps:

[0078] The leader drone conducts environmental monitoring, provides leader parameters, and locates its own coordinates and the destination coordinates through GPS;

[0079] The leader drone uses the particle swarm optimization algorithm to optimize and adjust the flight trajectory and determine the subsequent flight trajectory;

[0080] Every 5-10 minutes, the leader UAV's own coordinate position is used to determine whether 90% of the subsequent flight trajectory has been completed. If completed, the subsequent steps are carried out and a nearly completed signal is output to the flight control module 4. If not completed, the flight continues;

[0081] Repeat the above steps.

[0082] The leader drone optimizes and adjusts the flight trajectory through the particle swarm optimization algorithm, which not only improves the flight efficiency of the entire drone cluster and completes the corresponding flight mission with higher efficiency and shorter time, but also sends a start signal in advance for the subsequent flight control module 4 to adjust the two positions of the leader drone and the communication drone in the entire drone cluster, ensuring that each time after adjusting the subsequent part of the flight trajectory, the leader drone can maintain as many states as possible and the communication drone can maintain the best signal state as possible.

[0083] Preferably, the flight control module 4 is used to determine whether to replace the original leader drone with the remaining drones in the drone cluster and the best choice for replacing the original leader drone according to the drone endurance information in the drone cluster before each flight trajectory adjustment, including the following steps:

[0084] Receive the signal from the drone that is about to be completed, and calculate the remaining power of each drone according to its current remaining power and the average remaining power E avg Determine whether the remaining battery power of the leader drone is less than the average remaining battery power E avg , if the remaining battery of the leader drone is greater than the average remaining battery E avg , the original leader drone is maintained. If the remaining battery power of the leader drone is less than the average remaining battery power E avg , then select an ordinary drone to replace the original leader drone;

[0085] The power consumption E required for each ordinary drone to replace the original leader drone is calculated based on the leader parameters, team member parameters, and environmental parameters. c ;

[0086] Combined with the power consumption of each ordinary drone to replace the original leader drone E c The remaining power of each ordinary drone [E lead ,E com ,E1,E2,…,E n ], and obtain the remaining power of each ordinary drone after the replacement [E 1-c ,E 2-c ,…,E n-c ];

[0087] After the swap, the remaining power of each common drone [E 1-c ,E 2-c ,…,E n-c ] are sorted in descending order, and the first ranked ordinary drone is selected to replace the leader drone, and the leader drone replaces the ordinary drone.

[0088] The power consumption E required for each ordinary drone to replace the original leader drone is calculated based on the leader parameters, team member parameters, and environmental parameters. c , including the following steps,

[0089] Combine wind speed and relative position between ordinary drone and leader drone to correct the actual flight speed V of ordinary drone e , V e =V e +V wind ×cos(θ), where θ is the angle between wind direction and flight direction;

[0090] Simulate the flight time t of each ordinary drone flying to the original leader drone position f ,

[0091] Calculate the lift L of the ordinary drone flying to the original leader drone’s position, L = W f ;

[0092] Calculate the drag of a normal drone flying to the original leader drone's position Where S is the total surface area of ​​the UAV;

[0093] Calculate the power E required for each ordinary drone to replace the original leader drone c ,

[0094] The remaining power of each common drone [E lead ,E com ,E1,E2,…,E n ] minus the power consumption E required for each ordinary drone to replace the original leader drone c , and obtain the remaining power of each ordinary drone after the replacement [E 1-c ,E 2-c ,…,E n-c ].

[0095] Through the above method, the flight control module 4 can simulate in advance the electric energy required for each ordinary drone to switch to the position of the original leader drone, as well as the remaining electric energy after each ordinary drone switches to the position of the original leader drone, thereby ensuring that the ordinary drone that is finally switched to the position of the original leader drone can still maintain a good state after the displacement, providing the best choice for the replacement of the leader drone position, thereby enabling the entire drone cluster to maintain work for a longer period of time and reasonably allocating the power supply of each drone.

[0096] Preferably, if Figure 1 As shown, it also includes a communication module 5, which is connected to the flight monitoring module 1, the endurance monitoring module 2, the trajectory comparison module 3, and the flight control module 4. The communication module 5 is used for signal transmission, collecting the signal strength of each ordinary drone, and judging whether there is a position with a better signal than the original communication drone according to the drone endurance information, the flight parameters of each drone, and the flight formation of the drone cluster before each flight trajectory adjustment, and switching the corresponding ordinary drone to the current communication drone.

[0097] The communication module 5 is used for signal transmission, collecting the signal strength of each ordinary drone, and judging whether there is a position with better signal than the original communication drone according to the drone endurance information, flight parameters of each drone, and flight formation of the drone cluster before each flight trajectory adjustment, and switching the corresponding ordinary drone to the current communication drone, including the following steps:

[0098] Extract the distance D between the leader drone and the communication drone;

[0099] Extract the distance D between the ordinary drone and the communication drone w ;

[0100] Calculate the signal strength from the leader drone to the communication drone Calculate the signal strength from the communication drone to each regular drone Where K is a constant;

[0101] A comprehensive signal quality index Q is set to evaluate the effect of communication drones at different locations.

[0102] Traverse the position of each ordinary drone, use it as the position of the communication drone and calculate to find the drone coordinates at the maximum comprehensive signal quality index Q;

[0103] Determine whether the coordinates of the drone at the maximum comprehensive signal quality index Q are consistent with the coordinates of the original communication drone. If they are consistent, maintain the original state. If they are inconsistent, switch the ordinary drone at the coordinates of the drone at the maximum comprehensive signal quality index Q to the current communication drone.

[0104] Similarly, the above method can ensure that no matter what flight formation the entire drone cluster is in, no matter which ordinary drone replaces the original leader drone, the communication module 5 can find the drone position with the best signal in the entire drone cluster, and use the ordinary drone or the original communication drone at this position as the current communication drone, so that the entire drone cluster can maintain good communication effects and is less likely to have signal disconnection or unclear situations.

[0105] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A drone power management system, characterized in that: The invention comprises a flight monitoring module (1), a cruising range monitoring module (2), a trajectory comparison module (3), and a flight control module (4); the flight monitoring module (1), the cruising range monitoring module (2), and the trajectory comparison module (3) are all connected to the flight control module (4) in communication; the flight monitoring module (1) and the cruising range monitoring module (2) are also connected to the trajectory comparison module in communication; the flight monitoring module (1) is used to collect flight parameters of each unmanned aerial vehicle in the unmanned aerial vehicle cluster and the flight formation of the unmanned aerial vehicle cluster and feed them back to the flight control module (4); the cruising range monitoring module (2) is used to collect cruising range information of each unmanned aerial vehicle in the unmanned aerial vehicle cluster and feed it back to the flight control module (4); the trajectory comparison module (3) is used to judge the current flight trajectory process, formulate an adjusted flight trajectory, and feed it back to the flight control module (4); the flight control module (4) is used to judge whether to replace the original leader unmanned aerial vehicle with the remaining unmanned aerial vehicles in the unmanned aerial vehicle cluster and the best choice for replacing the original leader unmanned aerial vehicle according to the cruising range information of the unmanned aerial vehicles in the unmanned aerial vehicle cluster before each flight trajectory adjustment.

2. The UAV power management system according to claim 1, characterized in that: The flight monitoring module (1) is used to collect the flight parameters of each drone in the drone cluster and the flight formation of the drone cluster and feed them back to the flight control module (4), and comprises the following steps: A drone cluster is defined as a leader drone, a communication drone, and several common drones, wherein the leader drone is connected to the common drones through the communication drone; The flight parameters are defined as leader parameters, team member parameters, and environmental parameters. The leader parameters include the flight speed V of the leader drone. lead , the team member parameters include the flight speed V of the ordinary drone f , drag coefficient C Df , Load weight W f , and acceleration A f , the environmental parameters include wind speed V wind , wind direction, and air density ρ; The real-time flight parameters of the leader UAV and other common UAVs are collected and fed back to the flight control module (4).

3. The UAV power management system according to claim 2, characterized in that: The flight monitoring module (1) is used to collect the flight parameters of each drone in the drone cluster and the flight formation of the drone cluster and feed them back to the flight control module (4), and also includes the following steps: The leader drone generates a flight formation and shares it with several ordinary drones via the communication drone; The leader drone is used as the origin to establish spatial coordinates in combination with the flight formation, and the communication drone and several ordinary drones are used to generate the coordinate points (x, y, z) of each drone; The distance between each common drone and the leader drone is calculated and fed back to the flight control module (4). The distance between each common UAV and the communication UAV is calculated and fed back to the flight control module (4).

4. The UAV power management system according to claim 3, characterized in that: The flight monitoring module (1) is used to collect the flight parameters of each drone in the drone cluster and the flight formation of the drone cluster and feed them back to the flight control module (4), and also includes the following steps: The leader drone generates a flight formation and shares it with several ordinary drones via the communication drone; The leader drone is used as the origin to establish spatial coordinates in combination with the flight formation, and the communication drone and several ordinary drones are used to generate the coordinate points (x, y, z) of each drone; The distance between each common drone and the leader drone is calculated and fed back to the flight control module (4). The distance between each common UAV and the communication UAV is calculated and fed back to the flight control module (4).

5. The UAV power management system according to claim 4, characterized in that: The trajectory comparison module (3) is used to determine the current flight trajectory process, formulate an adjusted flight trajectory and feed it back to the flight control module (4), and includes the following steps: The leader drone conducts environmental monitoring, provides leader parameters, and locates its own coordinates and the destination coordinates through GPS; The leader drone uses the particle swarm optimization algorithm to optimize and adjust the flight trajectory and determine the subsequent flight trajectory; Every 5-10 minutes, the leader UAV's own coordinate position is used to determine whether 90% of the subsequent flight trajectory has been completed. If completed, the subsequent steps are carried out and a nearly completed signal is output to the flight control module (4). If not completed, the flight continues; Repeat the above steps.

6. The UAV power management system according to claim 5, characterized in that: The flight control module (4) is used to determine whether to replace the original leader drone with the remaining drones in the drone cluster and the best choice for replacing the original leader drone according to the endurance information of the drones in the drone cluster before each flight trajectory adjustment, and comprises the following steps: Receive the signal from the drone that is about to be completed, and calculate the remaining power of each drone according to its current remaining power and the average remaining power E avg Determine whether the remaining battery power of the leader drone is less than the average remaining battery power E avg , if the remaining battery of the leader drone is greater than the average remaining battery E avg , the original leader drone is maintained. If the remaining battery power of the leader drone is less than the average remaining battery power E avg , then select an ordinary drone to replace the original leader drone; The power consumption E required for each ordinary drone to replace the original leader drone is calculated through the leader parameters, team member parameters, and environmental parameters. c ; Combined with the power consumption of each ordinary drone to replace the original leader drone E c The remaining power of each ordinary drone [E lead ,E com ,E1,E2,…,E n ], and obtain the remaining power of each ordinary drone after the replacement [E 1-c ,E 2-c ,…,E n-c ]; After the swap, the remaining power of each common drone [E 1-c ,E 2-c ,…,E n-c ] are sorted in descending order, and the first ranked ordinary drone is selected to replace the leader drone, and the leader drone replaces the ordinary drone.

7. The UAV power management system according to claim 6, characterized in that: The power consumption E required for each ordinary drone to replace the original leader drone is calculated by using the leader parameters, team member parameters, and environmental parameters. c , including the following steps, Combine wind speed and relative position between ordinary drone and leader drone to correct the actual flight speed V of ordinary drone e , V e =V e +V wind ×cos(θ), where θ is the angle between wind direction and flight direction; Simulate the flight time t of each ordinary drone flying to the original leader drone position f , Calculate the lift L of the ordinary drone flying to the original leader drone’s position, L = W f ; Calculate the drag of a normal drone flying to the original leader drone's position Where S is the total surface area of ​​the UAV; Calculate the power E required for each ordinary drone to replace the original leader drone c , The remaining power of each common drone [E lead ,E com ,E1,E2,…,E n ] minus the power consumption E required for each ordinary drone to replace the original leader drone c , and obtain the remaining power of each ordinary drone after the replacement [E 1-c ,E 2-c ,…,E n-c ].

8. The UAV power management system according to claim 5, characterized in that: The device also comprises a communication module (5), wherein the communication module (5) is in communication connection with the flight monitoring module (1), the endurance monitoring module (2), the trajectory comparison module (3), and the flight control module (4), and the communication module (5) is used for signal transmission, collecting the signal strength of each common unmanned aerial vehicle, and determining whether there is a position with a better signal than the original communication unmanned aerial vehicle according to the endurance information of the unmanned aerial vehicles in the unmanned aerial vehicle cluster, the flight parameters of each unmanned aerial vehicle, and the flight formation of the unmanned aerial vehicle cluster before each flight trajectory adjustment, and switching the corresponding common unmanned aerial vehicle to the current communication unmanned aerial vehicle.

9. The UAV power management system according to claim 8, characterized in that: The communication module (5) is used for signal transmission, collecting the signal strength of each common drone, and determining whether there is a position with a better signal than the original communication drone according to the drone endurance information, the flight parameters of each drone, and the flight formation of the drone cluster before each flight trajectory adjustment, and switching the corresponding common drone to the current communication drone, including the following steps: Extract the distance D between the leader drone and the communication drone; Extract the distance D between the ordinary drone and the communication drone w ; Calculate the signal strength from the leader drone to the communication drone Calculate the signal strength from the communication drone to each regular drone Where K is a constant; A comprehensive signal quality index Q is set to evaluate the effect of communication drones at different locations. Traverse the position of each ordinary drone, use it as the position of the communication drone and calculate to find the drone coordinates at the maximum comprehensive signal quality index Q; Determine whether the coordinates of the drone at the maximum comprehensive signal quality index Q are consistent with the coordinates of the original communication drone. If they are consistent, maintain the original state. If they are inconsistent, switch the ordinary drone at the coordinates of the drone at the maximum comprehensive signal quality index Q to the current communication drone.

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