Unmanned aerial vehicle hangar and unmanned aerial vehicle charging method and system

Abstract

The invention discloses an unmanned aerial vehicle hangar and an unmanned aerial vehicle charging method and system, and relates to the technical field of unmanned aerial vehicle hangars and unmanned aerial vehicle charging. Analyzing the distance evaluation coefficient of each idle unmanned aerial vehicle library based on the spatial position coordinates; acquiring an environment evaluation coefficient of the unmanned aerial vehicle library output by the target unmanned aerial vehicle library, and judging a charging environment; and constructing a battery charging evaluation coefficient mathematical model of the unmanned aerial vehicle at each data acquisition time point, and judging the charging condition. According to the unmanned aerial vehicle hangar and the unmanned aerial vehicle charging method provided by the invention, by analyzing the unmanned aerial vehicle data and the spatial position coordinates of each idle unmanned aerial vehicle hangar, the safety analysis in the unmanned aerial vehicle charging process is realized, various different charging powers are set for each charging position in the unmanned aerial vehicle hangar, the operation efficiency of the unmanned aerial vehicle is improved, and the charging efficiency of the unmanned aerial vehicle is improved. The unmanned aerial vehicle charging system achieves better effects in the aspects of safety in the charging process of the unmanned aerial vehicle, operation efficiency of the unmanned aerial vehicle and service life maintenance of a battery of the unmanned aerial vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle hangar and unmanned aerial vehicle charging, in particular to an unmanned aerial vehicle hangar, an unmanned aerial vehicle charging method and system. BACKGROUND

[0002] In recent years, with the rapid development of unmanned aerial vehicle technology, unmanned aerial vehicles are increasingly widely used in various industries, including agricultural monitoring, urban planning, express delivery and disaster relief. However, as the frequency of use and the range of application of unmanned aerial vehicles expand, how to efficiently and safely charge and store unmanned aerial vehicles has become a problem to be solved. Traditional unmanned aerial vehicle charging methods mostly rely on manual operation, which is low in charging efficiency and has certain safety hazards.

[0003] Although unmanned aerial vehicle hangar technology has made certain progress, there are still many deficiencies in practical application. First, in the management of unmanned aerial vehicle charging, existing technology often only considers basic power supply, ignoring the actual state of the unmanned aerial vehicle battery and environmental factors. For example, the health status of different unmanned aerial vehicle batteries, environmental temperature and humidity, etc. will affect the charging efficiency and safety. However, most of the existing unmanned aerial vehicle hangar systems lack comprehensive consideration and dynamic adjustment capability for these factors, resulting in low charging efficiency, long charging time, and even possible charging failure and safety problems.

[0004] Secondly, the existing technology also has certain limitations in the space management of unmanned aerial vehicle hangar. Traditional unmanned aerial vehicle hangars usually use fixed storage locations and charging methods, which cannot be flexibly adjusted according to the real-time state and location of the unmanned aerial vehicle. This not only causes low space utilization, but also increases the complexity of unmanned aerial vehicle scheduling and management. Especially in the case of multiple unmanned aerial vehicles needing to be charged and stored at the same time, the existing technology is difficult to provide an efficient solution, often requiring manual intervention and complex scheduling management. SUMMARY

[0005] In view of the above problems, the present application is proposed.

[0006] Therefore, the technical problem solved by the present application is that the existing unmanned aerial vehicle hangar and unmanned aerial vehicle charging method has low safety during the unmanned aerial vehicle charging process, low unmanned aerial vehicle operation efficiency, cannot analyze the best target unmanned aerial vehicle hangar, and has poor battery life maintenance of the unmanned aerial vehicle.

[0007] To solve the above technical problems, the application provides the following technical scheme: a kind of unmanned aerial vehicle hangar and unmanned aerial vehicle charging method, including collecting unmanned aerial vehicle data;Based on spatial position coordinate analysis each idle unmanned aerial vehicle hangar distance evaluation coefficient;Collect target unmanned aerial vehicle hangar output unmanned aerial vehicle hangar environmental evaluation coefficient and judge charging environment;Unmanned aerial vehicle battery charging evaluation coefficient mathematical model is constructed at each data collection time point and charging condition is judged.

[0008] As a preferred scheme of the unmanned aerial vehicle hangar and the unmanned aerial vehicle charging method of the application, wherein: the unmanned aerial vehicle data collection includes collecting the battery charging temperature threshold, the rated power value, the remaining power value, the rated charging current, the spatial position coordinate and the next task spatial position coordinate of the unmanned aerial vehicle;

[0009] The spatial position coordinates of each idle unmanned aerial vehicle hangar are collected, including, according to the rated charging current of the unmanned aerial vehicle, obtaining the charging power of the idle and unreserved charging position in the unmanned aerial vehicle hangar, when the charging power of the idle and unreserved charging position in the unmanned aerial vehicle hangar is equal to the rated charging current of the unmanned aerial vehicle, the unmanned aerial vehicle hangar is recorded as an idle unmanned aerial vehicle hangar, thereby obtaining each idle unmanned aerial vehicle hangar, and obtaining the spatial position coordinates of each idle unmanned aerial vehicle hangar in the database.

[0010] As a preferred scheme of the unmanned aerial vehicle hangar and the unmanned aerial vehicle charging method of the application, wherein: the spatial position coordinate analysis based on each idle unmanned aerial vehicle hangar distance evaluation coefficient includes analyzing the output of each idle unmanned aerial vehicle hangar distance evaluation coefficient, the spatial position coordinates of the unmanned aerial vehicle and the next task spatial position coordinates are recorded as (X 1 ,Y 1 ,Z 1 ) and (X 2 ,Y 2 ,Z 2 ) respectively, and the spatial position coordinates of each idle unmanned aerial vehicle hangar are recorded as (X i 3 ,Y i 3 ,Z i 3 ), i represents the corresponding number of each idle unmanned aerial vehicle hangar, i=1, 2,..., n, n represents the total number of idle unmanned aerial vehicle hangars, n is a natural integer greater than or equal to 1;

[0011] The idle unmanned aerial vehicle hangar distance evaluation coefficient is represented as:

[0012]

[0013] 0<σ1≤1,0<σ2≤1,σ1+σ2=1

[0014] Wherein, λ iS i represents the distance between the space position of the drone in the database and the space position of the next task and the space position of the idle drone hangar, and σ1 represents the weight factor corresponding to the distance between the space position of the drone in the database and the space position of the next task, and σ2 represents the weight factor corresponding to the distance between the space position of the drone in the database and the space position of the idle drone hangar.

[0015] As a preferred scheme of the unmanned aerial vehicle hangar and the unmanned aerial vehicle charging method, the collecting the environmental evaluation coefficient of the target unmanned aerial vehicle hangar and judging the charging environment comprises: sorting the distance evaluation coefficients of the idle unmanned aerial vehicle hangars from small to large, recording the unmanned aerial vehicle hangar corresponding to the smallest distance evaluation coefficient of the idle unmanned aerial vehicle hangar as the target unmanned aerial vehicle hangar, and sending a charging position reservation request of the unmanned aerial vehicle hangar to the control center according to the rated charging current of the unmanned aerial vehicle.

[0016] The temperature, humidity and hydrogen content of the unmanned aerial vehicle hangar are recorded as T, Q and H respectively, and substituted into the environmental evaluation coefficient mathematical model of the unmanned aerial vehicle hangar, and represented as:

[0017]

[0018] 0 < ω1 ≤ 1, 0 < ω2 ≤ 1, 0 < ω3 ≤ 1, ω1 + ω2 + ω3 = 1

[0019] Wherein, β represents the environmental evaluation coefficient of the unmanned aerial vehicle hangar, T', Q' and H' represent the reference value of the temperature, the reference value of the humidity and the reference value of the hydrogen content of the unmanned aerial vehicle hangar in the database respectively, T and Q represent the allowable floating value of the temperature and the allowable floating value of the humidity of the unmanned aerial vehicle hangar in the database respectively, ω1, ω2 and ω3 represent the weight factor corresponding to the temperature, the weight factor corresponding to the humidity and the weight factor corresponding to the hydrogen content of the unmanned aerial vehicle hangar in the database respectively.

[0020] As a preferred scheme of the unmanned aerial vehicle hangar and the unmanned aerial vehicle charging method, the constructing the battery charging evaluation coefficient mathematical model of the unmanned aerial vehicle at each data collection time point and judging the charging condition comprises: comparing the environmental evaluation coefficient of the unmanned aerial vehicle hangar with the environmental evaluation coefficient threshold in the database, when the environmental evaluation coefficient of the unmanned aerial vehicle hangar is greater than or equal to the environmental evaluation coefficient threshold in the database, it is judged that the unmanned aerial vehicle hangar does not meet the charging environment required by the unmanned aerial vehicle, otherwise it is judged that the unmanned aerial vehicle hangar meets the charging environment required by the unmanned aerial vehicle.

[0021] As a preferred scheme of the unmanned aerial vehicle hangar and the unmanned aerial vehicle charging method, the battery charging evaluation coefficient mathematical model of the unmanned aerial vehicle at each data acquisition time point is constructed and the charging condition is judged, including that the residual power value, the rated power value and the rated charging current in the unmanned aerial vehicle data are recorded as D, ED and EC respectively, and the battery power value of the unmanned aerial vehicle at each data acquisition time point is recorded as DL j , j represents the number corresponding to each data acquisition time point, j = 1, 2, …, n, n represents the total number of data acquisition time points, and n is an integer greater than or equal to 1;

[0022] The battery charging evaluation coefficient at the data acquisition time point is represented as:

[0023]

[0024] , wherein, represents the battery charging evaluation coefficient of the unmanned aerial vehicle at the jth data acquisition time point, e represents a natural constant, and E represents a reference value corresponding to the battery charging of the unmanned aerial vehicle in the database, represents a compensation factor corresponding to the battery charging evaluation coefficient at each data acquisition time point in the database.

[0025] As a preferred scheme of the unmanned aerial vehicle hangar and the unmanned aerial vehicle charging method, the battery charging evaluation coefficient mathematical model of the unmanned aerial vehicle at each data acquisition time point is constructed and the charging condition is judged, including that the battery charging evaluation coefficient of the unmanned aerial vehicle at each data acquisition time point is compared with the battery charging evaluation coefficient threshold in the database, when the battery charging evaluation coefficient at the data acquisition time point is greater than or equal to the battery charging evaluation coefficient threshold in the database, it is judged that the charging of the unmanned aerial vehicle at the data acquisition time point is abnormal, otherwise it is judged that the charging of the unmanned aerial vehicle at the data acquisition time point is not abnormal, so as to judge whether the charging of the unmanned aerial vehicle at each data acquisition time point is abnormal;

[0026] The control center sends a work command to the unmanned aerial vehicle hangar, and the unmanned aerial vehicle hangar executes the work command;

[0027] When the unmanned aerial vehicle hangar does not meet the charging environment required by the unmanned aerial vehicle, the environment evaluation coefficient of the unmanned aerial vehicle hangar is transmitted to the control center, the control center extracts the corresponding work command in the database according to the environment evaluation coefficient of the unmanned aerial vehicle hangar, and sends it to the unmanned aerial vehicle hangar, and the unmanned aerial vehicle hangar executes the work command;

[0028] When the charging of the unmanned aerial vehicle at the data acquisition time point is abnormal, the battery charging evaluation coefficient at the data acquisition time point is transmitted to the control center, the control center extracts the corresponding work command in the database according to the battery charging evaluation coefficient at the data acquisition time point, and sends it to the unmanned aerial vehicle hangar, and the unmanned aerial vehicle hangar executes the work command.

[0029] Another object of the present application is to provide a UAV hangar and UAV charging system which can collect the environmental evaluation coefficient of the target UAV hangar and judge the charging environment, thereby solving the problem of low work efficiency of the current UAV hangar and UAV charging method.

[0030] As a preferred scheme of the UAV hangar and UAV charging system, the scheme comprises a UAV information acquisition module, a UAV analysis module, a UAV hangar information acquisition module, a UAV hangar information analysis module, a charging information acquisition module, a charging information analysis module, and a work execution module. The UAV information acquisition module is configured to acquire UAV data and spatial position coordinates of each idle UAV hangar when the UAV sends a return-to-UAV-hangar request to the control center. The UAV analysis module is configured to analyze the distance evaluation coefficient of each idle UAV hangar based on the UAV data and the spatial position coordinates of each idle UAV hangar, and then acquire the target UAV hangar and send a target UAV hangar charging position reservation request to the control center. The UAV hangar information acquisition module is configured to acquire the battery temperature of the UAV when the UAV arrives at the charging position of the target UAV hangar, and acquire the temperature, humidity, and hydrogen content of the UAV hangar when the battery temperature of the UAV meets the battery charging temperature threshold. The UAV hangar information analysis module is configured to analyze the environmental evaluation coefficient of the UAV hangar based on the environmental data of the UAV hangar when the battery temperature of the UAV meets the battery charging temperature threshold, and then judge whether the UAV hangar meets the required charging environment of the UAV. The charging information acquisition module is configured to extract the residual power value and the rated charging current in the UAV data when the UAV is charging in the UAV hangar, and set each data acquisition time point based on the residual power value of the UAV by the control center, and then acquire the battery power value and the temperature at each data acquisition time point. The charging information analysis module is configured to analyze the battery charging evaluation coefficient of the UAV at each data acquisition time point when the temperature at each data acquisition time point meets the battery charging temperature threshold, and then judge whether the charging of the UAV at each data acquisition time point is abnormal. The work execution module is configured to transmit data to the control center when the UAV hangar does not meet the required charging environment of the UAV or the charging of the UAV at a certain data acquisition time point is abnormal, and the control center sends a corresponding work command to the UAV hangar, and the UAV hangar executes the work command.

[0031] A computer device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the steps of the UAV hangar and UAV charging method.

[0032] A computer readable storage medium, having stored thereon a computer program, the computer program being executed by a processor to implement the steps of the unmanned aerial vehicle hangar and unmanned aerial vehicle charging method.

[0033] The unmanned aerial vehicle hangar and unmanned aerial vehicle charging method provided by the application can obtain a target unmanned aerial vehicle hangar by analyzing unmanned aerial vehicle data and spatial position coordinates of each idle unmanned aerial vehicle hangar, and send a target unmanned aerial vehicle hangar charging position reservation request to a control center, and then analyze environmental data of the unmanned aerial vehicle hangar when the unmanned aerial vehicle meets the charging condition, solve the limitations in the current unmanned aerial vehicle hangar charging development feasibility analysis process, set each data collection time point to collect unmanned aerial vehicle data, analyze the safety of the unmanned aerial vehicle charging process, set different charging powers for each charging position in the unmanned aerial vehicle hangar, which is beneficial to different types of unmanned aerial vehicles to obtain the required optimal charging power, so that the unmanned aerial vehicle can be quickly charged, thereby saving the charging time of the unmanned aerial vehicle, enabling the unmanned aerial vehicle to start the next task faster, and improving the operation efficiency of the unmanned aerial vehicle to a certain extent, obtaining a target unmanned aerial vehicle hangar according to the positions of the unmanned aerial vehicle and the unmanned aerial vehicle hangar, comprehensively analyzing the distance of the optimal target unmanned aerial vehicle hangar according to the unmanned aerial vehicle, the unmanned aerial vehicle hangar and the next task position, saving the power of the unmanned aerial vehicle to a certain extent, saving the flight distance of the unmanned aerial vehicle, setting each data collection time point according to the remaining power value of the unmanned aerial vehicle, analyzing the charging condition of the unmanned aerial vehicle, when the temperature at a certain data collection time point meets the battery charging temperature threshold, the next charging condition analysis is performed, ensuring that the unmanned aerial vehicle at each time point maintains a safe and stable state, otherwise, when the temperature at a certain data collection time point does not meet the battery charging temperature threshold, the charging of the unmanned aerial vehicle is stopped, and the corresponding cold air discharge is performed by the control center, which is helpful to maintain the service life of the battery of the unmanned aerial vehicle. The application achieves better effects in the safety of the unmanned aerial vehicle charging process, the operation efficiency of the unmanned aerial vehicle and the service life maintenance of the battery of the unmanned aerial vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0035] Figure 1 The overall flowchart of the unmanned aerial vehicle hangar and unmanned aerial vehicle charging method provided by the first embodiment of the application.

[0036] Figure 2 The structural connection schematic diagram of the unmanned aerial vehicle hangar and unmanned aerial vehicle charging system provided by the third embodiment of the application. DETAILED DESCRIPTION

[0037] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the present application.

[0038] Embodiment 1, refer to Figure 1 For an embodiment of the present application, a UAV hangar and a UAV charging method are provided, comprising:

[0039] S1: Collecting UAV data.

[0040] Further, the UAV data includes the battery charging temperature threshold value, the rated power value, the residual power value, the rated charging current, the space position coordinate and the next task space position coordinate of the UAV.

[0041] S2: Analyzing the distance evaluation coefficient of each idle UAV hangar based on the space position coordinate.

[0042] Further, the space position coordinates of each idle UAV hangar are obtained, and the specific obtaining process is as follows: according to the rated charging current of the UAV, the charging power of the idle and unreserved charging position in the UAV hangar is obtained, when the charging power of the idle and unreserved charging position in a certain UAV hangar is equal to the rated charging current of the UAV, the UAV hangar is recorded as an idle UAV hangar, thereby obtaining each idle UAV hangar, and obtaining the space position coordinates of each idle UAV hangar in the database.

[0043] It should be noted that different UAVs may use different batteries and different rated charging currents, some support 22W and some support 33W, and when the charging power is equal to the rated power, the charging effect is best.

[0044] The charging space provided by the UAV hangar can accommodate most models of UAVs, and basically there is no need to consider the problem that the UAV cannot enter the charging position.

[0045] It should also be noted that each charging position in the UAV hangar is provided with a plurality of different charging powers, which is beneficial to different types of UAVs to obtain the required optimal charging power, so that the UAV can be quickly charged, thereby saving the charging time of the UAV, enabling the UAV to start the next task faster, and to a certain extent, improving the operation efficiency of the UAV.

[0046] Further, the space position coordinate of the UAV and the next task space position coordinate are respectively recorded as (X 1 ,Y1 1 ) and (X 2 2 2 i 3 i 3 i 3 ), wherein i represents the corresponding number of each idle UAV warehouse, i = 1, 2, …, n, n represents the total number of idle UAV warehouses, and n is a natural integer greater than or equal to 1.

[0047] The distance evaluation coefficient of the idle UAV warehouse is represented as:

[0048]

[0049] wherein λ i represents the distance evaluation coefficient of the i-th idle UAV warehouse, wherein S represents a reference value of the distance between the spatial position of the UAV in the database and the spatial position of the next task and the spatial position of the idle UAV warehouse, σ1represents a weight factor corresponding to the distance between the spatial position of the UAV in the database and the spatial position of the next task, and σ2represents a weight factor corresponding to the distance between the spatial position of the UAV in the database and the spatial position of the idle UAV warehouse.

[0050] It should be noted that 0 < σ1≤ 1, 0 < σ2≤ 1, and σ1+ σ2 = 1.

[0051] It should also be noted that the weight factor corresponding to the distance between the spatial position of the UAV and the spatial position of the next task and the weight factor corresponding to the distance between the spatial position of the UAV and the spatial position of the idle UAV warehouse are obtained by factor analysis method. First, the information of the distance between the spatial position of the UAV and the spatial position of the next task and the distance between the spatial position of the UAV and the spatial position of the idle UAV warehouse is condensed, and then the variance explanation rate after rotation is obtained, and the weight is obtained by accumulating the variance explanation rate.

[0052] S3: Collect the environmental evaluation coefficient of the target UAV warehouse output UAV warehouse and judge the charging environment.

[0053] Further, the temperature, humidity and hydrogen content of the UAV warehouse are represented as T, Q and H respectively, which are substituted into the mathematical model of the environmental evaluation coefficient of the UAV warehouse, and are represented as:

[0054]

[0055] ​​​​​​Wherein, β represents the environmental evaluation coefficient of the UAV warehouse, T', Q' and H' represent the reference value of the temperature, the reference value of the humidity and the reference value of the hydrogen content of the UAV warehouse in the database respectively, T and Q represent the allowable floating value of the temperature and the allowable floating value of the humidity of the UAV warehouse in the database respectively, ω1, ω2 and ω3 represent the weight factor corresponding to the temperature, the weight factor corresponding to the humidity and the weight factor corresponding to the hydrogen content of the UAV warehouse in the database respectively.

[0056] It should be noted that 0 < ω1 ≤ 1, 0 < ω2 ≤ 1, 0 < ω3 ≤ 1, ω1 + ω2 + ω3 = 1.

[0057] It should also be noted that the weight factor corresponding to the temperature, the weight factor corresponding to the humidity and the weight factor corresponding to the hydrogen content of the UAV warehouse are obtained by factor analysis method, first the information condensation of the temperature, humidity and hydrogen content of the UAV warehouse is carried out, then the variance explained rate after rotation is obtained, and the weight is obtained by accumulating the variance explained rate.

[0058] S4: Constructing the battery charging evaluation coefficient mathematical model of the UAV at each data collection time point and judging the charging condition.

[0059] Further, the residual capacity value, the rated capacity value and the rated charging current in the UAV data are denoted as D, ED and EC respectively, and the UAV battery capacity value at each data collection time point is denoted as DL j , j represents the number corresponding to each data collection time point, j = 1, 2,..., n, n represents the total number of data collection time points, n is an integer greater than or equal to 1;

[0060] The battery charging evaluation coefficient at the data collection time point is denoted as:

[0061]

[0062] Wherein, represents the battery charging evaluation coefficient of the UAV at the jth data collection time point, e represents the natural constant, E represents the reference value of the battery charging of the UAV in the database, represents the compensation factor corresponding to the battery charging evaluation coefficient at each data collection time point in the database.

[0063] It should be noted that,

[0064] It should also be noted that the compensation factor corresponding to the battery charging evaluation coefficient at each data collection time point in the database is obtained, and the higher the temperature, the greater the compensation factor of the battery charging evaluation coefficient.

[0065] Further, the battery charging evaluation coefficient of the unmanned aerial vehicle at each data collection time point is compared with the battery charging evaluation coefficient threshold in the database. When the battery charging evaluation coefficient at a certain data collection time point is greater than or equal to the battery charging evaluation coefficient threshold in the database, it is judged that the charging of the unmanned aerial vehicle at the data collection time point is abnormal, otherwise it is judged that the charging of the unmanned aerial vehicle at the data collection time point is not abnormal, thereby judging whether the charging of the unmanned aerial vehicle at each data collection time point is abnormal.

[0066] It should be noted that the charging condition of the unmanned aerial vehicle is analyzed according to the residual power value of the unmanned aerial vehicle. When the temperature at a certain data collection time point meets the battery charging temperature threshold, the next step of analyzing the charging condition is performed, which ensures that the unmanned aerial vehicle at each time point maintains a safe and stable state, otherwise when the temperature at a certain data collection time point does not meet the battery charging temperature threshold, the charging of the unmanned aerial vehicle is stopped, and the corresponding cold air discharge is performed by the control center, which helps to maintain the service life of the battery of the unmanned aerial vehicle.

[0067] It should also be noted that when the unmanned aerial vehicle warehouse does not meet the charging environment required by the unmanned aerial vehicle, the environment evaluation coefficient of the unmanned aerial vehicle warehouse is transmitted to the control center, the control center extracts the corresponding operation command in the database according to the environment evaluation coefficient of the unmanned aerial vehicle warehouse, and sends it to the unmanned aerial vehicle warehouse. The unmanned aerial vehicle warehouse executes the operation command; when the charging of the unmanned aerial vehicle at a certain data collection time point is abnormal, the battery charging evaluation coefficient at the data collection time point is transmitted to the control center, and the control center extracts the corresponding operation command in the database according to the battery charging evaluation coefficient at the data collection time point, and sends it to the unmanned aerial vehicle warehouse. The unmanned aerial vehicle warehouse executes the operation command.

[0068] Further, by analyzing the unmanned aerial vehicle data and the spatial position coordinates of each idle unmanned aerial vehicle warehouse, the target unmanned aerial vehicle warehouse is obtained, and a target unmanned aerial vehicle warehouse charging position reservation request is sent to the control center, and then when the unmanned aerial vehicle meets the charging condition, the environment data of the unmanned aerial vehicle warehouse is analyzed, which solves the limitation problem existing in the current unmanned aerial vehicle warehouse charging development feasibility analysis process, sets each data collection time point to collect unmanned aerial vehicle data, and realizes the safety analysis of the unmanned aerial vehicle charging process.

[0069] In embodiment 2, an embodiment of the present application provides an unmanned aerial vehicle hangar and an unmanned aerial vehicle charging method. In order to verify the beneficial effects of the present application, economic benefit calculation and simulation experiments are used for scientific demonstration.

[0070] Firstly, the experimental objects include 10 unmanned aerial vehicles and 5 unmanned aerial vehicle hangars.

[0071] • Before the experiment begins, data collection is performed for each drone, including initial battery level and current position coordinates (XYZ). These data are monitored and recorded in real-time by sensors installed on the drones and transmitted to the central control system.

[0072] Distance evaluation (experimental group): Based on the current position coordinates of the drones, the central control system calculates the distance evaluation coefficient of each drone to each drone warehouse. The system selects the drone warehouse with the shortest distance as the target charging warehouse by comprehensively analyzing the distance data of all drone warehouses.

[0073] Environmental evaluation (experimental group): The system collects environmental data of the target drone warehouse, including temperature, humidity, and air quality parameters. These data are input into the central control system for environmental evaluation to ensure that the drones charge in the best environment.

[0074] Charging evaluation (experimental group): The system constructs a battery charging evaluation model based on the current battery level and estimated charging time of the drones. By comprehensively analyzing the battery level and environmental data, the system determines whether each drone needs to be charged immediately or wait for a better opportunity to optimize charging efficiency and safety.

[0075] Charging process (experimental group): Based on the evaluation results, the drones that need to be charged are dispatched to the optimal drone warehouse for charging. During the charging process, the system continuously monitors the battery status and environmental parameters to ensure the safety and efficiency of the charging process.

[0076] Control group: The drones in the control group use existing technology for charging, i.e., without considering environmental factors and location optimization, directly charging operation.

[0077] Table 1 Experimental data table

[0078]

[0079] Table 2 Control group data table

[0080]

[0081] In terms of safety:

[0082] Experimental group: The initial battery level of drone 1 is 20%, and its charging evaluation coefficient is 0.25. Since the charging environment evaluation coefficient is 0.85, it indicates that charging is performed under good environmental conditions, effectively avoiding safety hazards such as overheating. During the charging process of drone 5, the environmental evaluation coefficient is 0.93, and the charging evaluation coefficient is 0.47, ensuring charging in the best environment and improving safety.

[0083] Control group: The initial power of UAV 6 is 22%, the charging evaluation coefficient is 0.20, and the environmental evaluation coefficient is 0.80, which shows that there is a safety hazard in the charging process without considering the environment and location optimization, which may cause the battery to overheat and damage.

[0084] In terms of work efficiency:

[0085] Experimental group: The initial power of UAV 3 is 50%, and its charging evaluation coefficient is 0.53, which is much higher than that of other UAVs, showing the high efficiency of charging in the best environment and location. The environmental evaluation coefficient of UAV 2 is 0.90, and the charging evaluation coefficient is 0.39, although the environment is good, but due to the long distance, the charging efficiency is slightly reduced.

[0086] Control group: The initial power of UAV 8 is 48%, the charging evaluation coefficient is 0.48, although the environmental evaluation coefficient is 0.90, but due to the lack of location optimization, the charging efficiency is not as good as that of UAV 3 in the experimental group.

[0087] In terms of battery life:

[0088] Experimental group: During the charging process of UAV 5, the environmental evaluation coefficient is 0.93, and the charging evaluation coefficient is 0.47, which shows the positive effect of charging in a good environment on the battery life. Although the environmental evaluation coefficient of UAV 2 is 0.90, the charging evaluation coefficient is only 0.39, and long-term charging in a sub-optimal environment may have a negative impact on the battery life.

[0089] Control group: The initial power of UAV 10 is 43%, the charging evaluation coefficient is 0.42, and the environmental evaluation coefficient is 0.88, although the environment is good, but due to the lack of location optimization management, the battery life is affected to a certain extent.

[0090] In summary, the present application has achieved better results in the safety of the UAV charging process, the work efficiency of the UAV, and the maintenance of the life of the UAV battery.

[0091] Example 3, refer to Figure 2 , an embodiment of the present application, provides a UAV hangar and a UAV charging system, which comprises a UAV information acquisition module, a UAV analysis module, a UAV hangar information acquisition module, a UAV hangar information analysis module, a charging information acquisition module, a charging information analysis module, and a work execution module.

[0092] The unmanned aerial vehicle information acquisition module is configured to acquire unmanned aerial vehicle data and spatial position coordinates of each idle unmanned aerial vehicle garage when the unmanned aerial vehicle sends a return unmanned aerial vehicle garage request to the control center; the unmanned aerial vehicle analysis module is configured to analyze distance evaluation coefficients of each idle unmanned aerial vehicle garage according to the unmanned aerial vehicle data and the spatial position coordinates of each idle unmanned aerial vehicle garage, and then acquire a target unmanned aerial vehicle garage and send a target unmanned aerial vehicle garage charging position reservation request to the control center; the unmanned aerial vehicle garage information acquisition module is configured to acquire a battery temperature of the unmanned aerial vehicle when the unmanned aerial vehicle arrives at the charging position of the target unmanned aerial vehicle garage; when the battery temperature of the unmanned aerial vehicle meets a battery charging temperature threshold, the unmanned aerial vehicle garage information acquisition module is configured to acquire a temperature, humidity and hydrogen content of the unmanned aerial vehicle garage; the unmanned aerial vehicle garage information analysis module is configured to analyze an environment evaluation coefficient of the unmanned aerial vehicle garage according to the environment data of the unmanned aerial vehicle garage when the battery temperature of the unmanned aerial vehicle meets the battery charging temperature threshold, so as to determine whether the unmanned aerial vehicle garage meets a required charging environment of the unmanned aerial vehicle; the charging information acquisition module is configured to extract a residual power value and a rated charging current in the unmanned aerial vehicle data when the unmanned aerial vehicle is charging in the unmanned aerial vehicle garage, and set each data acquisition time point according to the residual power value of the unmanned aerial vehicle by the control center, and then acquire a battery power value and a temperature of the unmanned aerial vehicle at each data acquisition time point; the charging information analysis module is configured to analyze a battery charging evaluation coefficient of the unmanned aerial vehicle at each data acquisition time point when the temperature at each data acquisition time point meets the battery charging temperature threshold, so as to determine whether the charging of the unmanned aerial vehicle at each data acquisition time point is abnormal; and the operation execution module is configured to transmit data to the control center when the unmanned aerial vehicle garage does not meet the required charging environment of the unmanned aerial vehicle or the charging of the unmanned aerial vehicle at a certain data acquisition time point is abnormal, and the control center sends a corresponding operation command to the unmanned aerial vehicle garage, and the unmanned aerial vehicle garage executes the operation command.

[0093] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0094] The logic and / or steps represented in the flow diagrams or otherwise described herein, for example, can be considered as a sequence of executable instructions, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. In the context of this specification, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium.

[0095] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can also be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that can be later executed by a computer. In some embodiments, the machine-readable medium can be a transmission line, a carrier wave, a signal, or a computer readable media embodied in an SGML, HTML, Extensible Markup Language (XML), or other markup language that communicates, or transmits, a program over or with the instructions being executed by a machine.

[0096] It should be understood that aspects of the application can be implemented in hardware, software, firmware or combinations thereof. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following techniques, which are well known in the art, can be used to implement the application: a hybrid of the techniques mentioned above; a combination of one or more of the techniques mentioned above; or one or more other techniques that will be apparent to those skilled in the art given the benefit of this disclosure. It is therefore anticipated that one of ordinary skill in the art will be able to practice the application with the disclosed acts, without undue experimentation.

[0097] It should be noted that the above examples are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced, without departing from the spirit and scope of the technical solutions of the present application, which should be covered in the scope of the claims of the present application.

Claims

1. A UAV hangar and UAV charging method, characterized in that, The method comprises the following steps: Collecting unmanned aerial vehicle data; Analyzing the distance evaluation coefficient of each idle unmanned aerial vehicle warehouse based on spatial position coordinates; Collecting the environmental evaluation coefficient of the target unmanned aerial vehicle warehouse and judging the charging environment; Constructing a mathematical model of the battery charging evaluation coefficient of the unmanned aerial vehicle at each data collection time point and judging the charging condition. 2.The UAV hangar and UAV charging method of claim 1, wherein: The collection of unmanned aerial vehicle data includes collecting the battery charging temperature threshold, rated power value, remaining power value, rated charging current, spatial position coordinates and next task spatial position coordinates of the unmanned aerial vehicle; Collecting the spatial position coordinates of each idle unmanned aerial vehicle warehouse, including obtaining the charging power of the idle and unreserved charging position in the unmanned aerial vehicle warehouse according to the rated charging current of the unmanned aerial vehicle, and when the charging power of the idle and unreserved charging position in the unmanned aerial vehicle warehouse is equal to the rated charging current of the unmanned aerial vehicle, the unmanned aerial vehicle warehouse is recorded as an idle unmanned aerial vehicle warehouse, thereby obtaining each idle unmanned aerial vehicle warehouse, and obtaining the spatial position coordinates of each idle unmanned aerial vehicle warehouse in the database. 3.The UAV hangar and UAV charging method of claim 2, wherein: The analyzing the distance evaluation coefficient of each idle UAV warehouse based on the spatial position coordinates comprises: outputting the distance evaluation coefficient of each idle UAV warehouse, taking the spatial position coordinates of the UAV and the spatial position coordinates of the next task as (X 1 ,Y 1 ,Z 1 ) and (X 2 ,Y 2 ,Z 2 ) respectively, and taking the spatial position coordinates of each idle UAV warehouse as (X i 3 ,Y i 3 ,Z i 3 ), wherein i represents the number corresponding to each idle UAV warehouse, i = 1, 2, …, n, n represents the total number of idle UAV warehouses, and n is a natural integer greater than or equal to 1. The distance evaluation coefficient of the idle unmanned aerial vehicle warehouse is represented as: wherein λ i represents the distance evaluation coefficient of the ith idle UAV hangar, S represents the reference value of the distance between the spatial position of the UAV in the database and the spatial position of the next task and the spatial position of the idle UAV hangar, σ1 represents the weight factor corresponding to the distance between the spatial position of the UAV in the database and the spatial position of the next task, and σ2 represents the weight factor corresponding to the distance between the spatial position of the UAV in the database and the spatial position of the idle UAV hangar. 4.The UAV hangar and UAV charging method of claim 3, wherein: The collection of the environmental evaluation coefficient of the target unmanned aerial vehicle warehouse and the judgment of the charging environment include sorting the distance evaluation coefficients of each idle unmanned aerial vehicle warehouse from small to large, recording the unmanned aerial vehicle warehouse corresponding to the smallest distance evaluation coefficient of the idle unmanned aerial vehicle warehouse as the target unmanned aerial vehicle warehouse, and sending a charging position reservation request of the unmanned aerial vehicle warehouse to the control center according to the rated charging current of the unmanned aerial vehicle; The temperature, humidity and hydrogen content of the unmanned aerial vehicle warehouse are recorded as T, Q and H respectively, and substituted into the environmental evaluation coefficient mathematical model of the unmanned aerial vehicle warehouse, represented as: Wherein, β represents the environmental evaluation coefficient of the unmanned aerial vehicle warehouse, T', Q' and H' represent the reference value of the temperature, the reference value of the humidity and the reference value of the hydrogen content of the unmanned aerial vehicle warehouse in the database respectively, T and Q represent the allowable floating value of the temperature and the allowable floating value of the humidity of the unmanned aerial vehicle warehouse in the database respectively, ω1, ω2 and ω3 represent the weight factor corresponding to the temperature, the weight factor corresponding to the humidity and the weight factor corresponding to the hydrogen content of the unmanned aerial vehicle warehouse in the database respectively. 5.The UAV hangar and UAV charging method of claim 4, wherein: The construction of the mathematical model of the battery charging evaluation coefficient of the unmanned aerial vehicle at each data collection time point and the judgment of the charging condition include comparing the environmental evaluation coefficient of the unmanned aerial vehicle warehouse with the environmental evaluation coefficient threshold in the database, when the environmental evaluation coefficient of the unmanned aerial vehicle warehouse is greater than or equal to the environmental evaluation coefficient threshold in the database, it is judged that the unmanned aerial vehicle warehouse does not meet the required charging environment of the unmanned aerial vehicle, otherwise it is judged that the unmanned aerial vehicle warehouse meets the required charging environment of the unmanned aerial vehicle. 6.The UAV hangar and UAV charging method of claim 5, wherein: The battery charging evaluation coefficient mathematical model of the constructed unmanned aerial vehicle at each data collection time point and the judgment of the charging condition include the residual power value, the rated power value and the rated charging current in the unmanned aerial vehicle data, which are respectively denoted as D, ED and EC, and the battery power value of the unmanned aerial vehicle at each data collection time point is denoted as DL j , j represents the number corresponding to each data collection time point, j = 1, 2,..., n, n represents the total number of data collection time points, and n is an integer greater than or equal to 1; The battery charging evaluation coefficient at the data collection time point is represented as: wherein, represents the battery charging evaluation coefficient of the unmanned aerial vehicle at the jth data collection time point, e represents a natural constant, and E represents a reference value corresponding to the battery charging of the unmanned aerial vehicle in the database, represents the compensation factor corresponding to the battery charging evaluation coefficient of each data collection time point in the database. 7.The UAV hangar and UAV charging method of claim 6, wherein: The construction of the mathematical model of the battery charging evaluation coefficient of the unmanned aerial vehicle at each data collection time point and the judgment of the charging condition include comparing the battery charging evaluation coefficient of the unmanned aerial vehicle at each data collection time point with the battery charging evaluation coefficient threshold in the database, when the battery charging evaluation coefficient at the data collection time point is greater than or equal to the battery charging evaluation coefficient threshold in the database, it is judged that the charging of the unmanned aerial vehicle at the data collection time point is abnormal, otherwise it is judged that the charging of the unmanned aerial vehicle at the data collection time point is not abnormal, thereby judging whether the charging of the unmanned aerial vehicle at each data collection time point is abnormal; The control center sends a work command to the drone warehouse, and the drone warehouse executes the work command; When the drone warehouse does not meet the charging environment required by the drone, the environmental evaluation coefficient of the drone warehouse is transmitted to the control center, the control center extracts the corresponding work command from the database according to the environmental evaluation coefficient of the drone warehouse, and sends it to the drone warehouse, and the drone warehouse executes the work command; When the charging of the drone at the data collection time point is abnormal, the battery charging evaluation coefficient at the data collection time point is transmitted to the control center, the control center extracts the corresponding work command from the database according to the battery charging evaluation coefficient at the data collection time point, and sends it to the drone warehouse, and the drone warehouse executes the work command.

8. A system employing the UAV hangar and the UAV charging method according to any one of claims 1-7, characterized in that: It comprises a drone information acquisition module, a drone analysis module, a drone warehouse information acquisition module, a drone warehouse information analysis module, a charging information acquisition module, a charging information analysis module, and a work execution module. The drone information acquisition module is used to acquire the drone data and the spatial position coordinates of each idle drone warehouse when the drone sends a return-to-drone-warehouse request to the master control center. The drone analysis module is used to analyze the distance evaluation coefficient of each idle drone warehouse according to the drone data and the spatial position coordinates of each idle drone warehouse, and then acquire the target drone warehouse and send a target drone warehouse charging position reservation request to the control center. The drone warehouse information acquisition module is used to acquire the battery temperature when the drone arrives at the charging position of the target drone warehouse, and acquire the temperature, humidity, and hydrogen content of the drone warehouse when the battery temperature of the drone meets the battery charging temperature threshold. The drone warehouse information analysis module is used to analyze the environmental evaluation coefficient of the drone warehouse according to the environmental data of the drone warehouse when the battery temperature of the drone meets the battery charging temperature threshold, so as to determine whether the drone warehouse meets the charging environment required by the drone. The charging information acquisition module is used to extract the remaining power value and the rated charging current in the drone data when the drone is charging in the drone warehouse, and set each data collection time point according to the remaining power value of the drone by the control center, and then acquire the battery power value and temperature of the drone at each data collection time point. The charging information analysis module is used to analyze the battery charging evaluation coefficient of the drone at each data collection time point when the temperature at each data collection time point meets the battery charging temperature threshold, so as to determine whether the charging of the drone at each data collection time point is abnormal. The work execution module is used to transmit the data to the control center when the drone warehouse does not meet the charging environment required by the drone or the charging of the drone at a certain data collection time point is abnormal, the control center sends a corresponding work command to the drone warehouse, and the drone warehouse executes the work command. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the drone warehouse and the drone charging method in any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the drone warehouse and the drone charging method in any one of claims 1 to 7.

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