Photovoltaic charging control method and system for unmanned aerial vehicle airport

Abstract

The invention relates to the technical field of solar power supply distribution, in particular to a photovoltaic charging control method and system for an unmanned aerial vehicle airport. The method comprises the following steps: firstly, acquiring a preset inspection path, unit inspection path power consumption, residual electric quantity and available electric quantity of an unmanned aerial vehicle airport on the same day of each unmanned aerial vehicle; further circularly acquiring the to-be-charged unmanned aerial vehicle, and judging whether the available power supply quantity of the airport meets the inspection requirements of all the unmanned aerial vehicles or not; when it is judged that the current-day available power supply quantity cannot meet the inspection requirements of all the unmanned aerial vehicles, the local replaceable degree of the target segmented path is obtained, deletion of the target segmented path is controlled, and a corrected inspection path of each to-be-charged unmanned aerial vehicle is obtained until it is judged that the current-day available power supply quantity can meet the inspection requirements of all the unmanned aerial vehicles; obtaining a final inspection path of each unmanned aerial vehicle; and finally, according to the final inspection path, the residual electric quantity, the unit inspection path power consumption and the available power supply quantity of each unmanned aerial vehicle, carrying out electric quantity distribution on each unmanned aerial vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of solar power supply distribution, and in particular to a photovoltaic charging control method and system for an unmanned aerial vehicle airport. Background Art

[0002] Photovoltaic power generation modules are deployed in drone airports to convert solar energy into electrical energy and transmit it to energy storage modules. The energy storage modules can provide inspection power for drones when performing inspection tasks to meet the inspection power needs of drones. However, the amount of power that the energy storage module can provide is affected by weather conditions. For example, when the weather conditions are long-day sunshine on sunny days compared to short-day sunshine on cloudy days, the efficiency and total amount of solar energy converted into electrical energy are higher, and the energy storage module can provide more sufficient power.

[0003] Since the storage capacity of the energy storage module has an upper limit and the conversion of solar energy is affected by weather factors, the stored power and the remaining power of the drones cannot meet the needs of all drones for complete inspections. Therefore, how to intelligently control photovoltaic charging and reasonably allocate the stored power to ensure the inspection effect becomes a key issue. Summary of the invention

[0004] In order to solve the technical problem of intelligently controlling photovoltaic charging to ensure inspection results, the purpose of the present invention is to provide a photovoltaic charging control method and system for drone airports. The technical solutions adopted are as follows:

[0005] A photovoltaic charging control method for a drone airport, the method comprising:

[0006] Obtain the preset inspection route of each drone, the power consumption per inspection distance, the remaining power, and the power available at the drone airport on that day;

[0007] Obtain the drones to be charged; determine whether the power supply at the airport on that day meets the inspection requirements of all drones based on the remaining power and the available power of all the drones to be charged, combined with the length of the preset inspection paths and the unit inspection distance of all the drones to be charged;

[0008] When it is determined that the power supply on that day cannot meet the inspection needs of all drones, the preset inspection path of any drone to be charged is selected as the target path; the overall substitutability of the target path is obtained according to the intersection characteristics of the target path and other preset inspection paths; the preset inspection path is segmented at the intersection points between the preset inspection paths to obtain segmented paths; any segmented path in the target path is selected as the target segmented path; the local substitutability of the target segmented path is obtained according to the intersection angle and path length between the target segmented path and other intersecting segmented paths, combined with the corresponding overall substitutability; the deletion of the target segmented path is controlled according to the local substitutability of the target segmented path, and the revised inspection path of each drone to be charged is obtained;

[0009] According to the latest revised inspection path of the drone to be charged, a new drone to be charged is obtained again. When it is re-determined that the power supply on that day cannot meet the inspection needs of all drones, the revised inspection path of the new drone to be charged is obtained again, until it is determined that the power supply on that day can meet the inspection needs of all drones, and the final inspection path of each drone is obtained;

[0010] Power is allocated to each drone according to the final inspection path, the remaining power, the power consumption per inspection distance and the available power of each drone.

[0011] Furthermore, the method for determining whether the power supply at the airport on that day meets the inspection requirements of all drones includes:

[0012] The sum of the available power and the remaining power of all the drones to be charged is taken as the total power;

[0013] The sum of the products of the lengths of the preset inspection paths of all the drones to be charged and the power consumption per unit inspection distance is taken as the total power demand;

[0014] When the total power is less than the total power demand, it is determined that the available power on that day cannot meet all drone inspection needs.

[0015] Furthermore, the method for obtaining the overall degree of substitutability includes:

[0016] Obtaining the number of intersections between the target path and other preset inspection paths;

[0017] Obtaining an intersection angle at the intersection of the target path and the other preset inspection paths; the intersection angle is the minimum intersection angle at the intersection of the two inspection paths;

[0018] The overall degree of substitutability of the target path is obtained according to the number of intersections corresponding to the target path and the intersection angles at all intersections; the number of intersections is positively correlated with the overall degree of substitutability; and the intersection angle is negatively correlated with the overall degree of substitutability.

[0019] Furthermore, the method for obtaining the local substitutability degree includes:

[0020] Select any segmented path that intersects with the target segmented path and belongs to other UAVs as a determination path; use the ratio of the length of the determination path to the length of the target segmented path as a replacement coefficient;

[0021] According to the intersection angle between the target segmented path and the determination path, the replacement coefficient and the overall degree of substitution of the target path, a local substitution coefficient of the target segmented path is obtained; the intersection angle is negatively correlated with the local substitution coefficient; the replacement coefficient and the overall degree of substitution are both positively correlated with the local substitution coefficient; the intersection angle between the target segmented path and the determination path is the same as the intersection angle between the target path to which the target segmented path belongs and the preset inspection path to which the determination path belongs at the corresponding intersection;

[0022] The maximum value of the local substitutability coefficients of the target segment path and all the determination paths is selected as the local substitutability degree of the target segment path.

[0023] Furthermore, the method of controlling the deletion of the target segmented path according to the local replaceability of the target segmented path to obtain the corrected inspection path of each of the unmanned aerial vehicles to be charged includes:

[0024] When the local replaceability is greater than a first preset threshold, it is determined that the corresponding target segmented path is deleted, and at the same time, the segmented path farthest from the airport and isolated in the target path is deleted, and the remaining path in the target path is used as the corrected inspection path corresponding to the drone to be charged.

[0025] Furthermore, when it is determined that the power supply on that day cannot meet the inspection needs of all drones, if the local substitutability of all the latest drones to be charged is less than or equal to the first preset threshold, or there is no intersection on the inspection path corresponding to all the latest drones to be charged, the shortest segmented path on the inspection path corresponding to all the latest drones to be charged is deleted, and the segmented path farthest from the airport and isolated is deleted to obtain the corrected inspection path of each drone to be charged.

[0026] Furthermore, the method for distributing power to each drone includes:

[0027] The product of the length of the final inspection path of each latest drone to be charged and the power consumption per unit inspection distance is used as the final power requirement of each latest drone to be charged; and power is allocated to the drones according to the final power requirement of each latest drone to be charged.

[0028] Furthermore, the method for obtaining the drone to be charged includes:

[0029] When the product of the preset inspection path corresponding to the drone and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, the corresponding drone is determined to be a drone to be charged.

[0030] Furthermore, the method for reacquiring a new drone to be charged includes:

[0031] If the product of the latest revised inspection path of the current drone to be charged and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, the corresponding drone is determined to be a new drone to be charged.

[0032] The present invention also proposes a photovoltaic charging control system for an unmanned aerial vehicle airport, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements any one of the steps of the photovoltaic charging control method for an unmanned aerial vehicle airport when executing the computer program.

[0033] The present invention has the following beneficial effects:

[0034] The present invention first obtains the preset inspection path of each drone, the power consumption per inspection distance, the remaining power and the power available at the drone airport on that day, and provides a data basis for analysis; further obtains the drone to be charged, determines whether the power available at the airport on that day meets the inspection needs of all drones, and provides a decision basis for whether to delete the inspection path in the future, and finally controls the photovoltaic charging; further, when it is determined that the power available on that day cannot meet the inspection needs of all drones, the overall substitutability of the target path is obtained according to the intersection characteristics of the target path and other preset inspection paths, and the substitutability of the target path is quantified from an overall perspective, so as to facilitate the subsequent priority deletion of paths with high substitutability and reduce the impact on the overall inspection area; further, according to the intersection angle and path length of the target segmented path and other intersecting segmented paths, combined with the corresponding overall substitutability, the overall situation is comprehensively analyzed. From the perspectives of part and whole, the local replaceability degree that characterizes the degree to which the target segmented path can be deleted is obtained, providing a basis for the subsequent control of the deletion of the target segmented path; further, according to the local replaceability degree of the target segmented path, the deletion of the target segmented path is controlled, and the revised inspection path of each unmanned aerial vehicle to be charged is obtained, and the available power of the energy storage module is dynamically adapted; further, it is determined in a circular manner whether the available power of the airport on that day meets the inspection requirements of all unmanned aerial vehicles, and the revised inspection path of the new unmanned aerial vehicle to be charged is obtained again, until it is determined that the available power on that day can meet the inspection requirements of all unmanned aerial vehicles, and the final inspection path of each unmanned aerial vehicle is obtained to adapt to the limitation of the available power of the energy storage module, providing a basis for the final optimization of power allocation; finally, according to the final inspection path, remaining power, power consumption per unit inspection distance and available power of each unmanned aerial vehicle, power allocation is performed for each unmanned aerial vehicle. When it is determined that the available power on that day is insufficient, the present invention analyzes the replaceability of the inspection path from the perspectives of part and whole, deletes the inspection path, ensures that the inspection of key areas is not affected, improves the flexibility and adaptability of the inspection task, and improves the energy utilization rate of the photovoltaic charging system in the unmanned aerial vehicle airport. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 A flowchart of a photovoltaic charging control method for a drone airport provided by one embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a preset inspection path of a drone provided by an embodiment of the present invention;

[0038] Figure 3 A schematic diagram of a patrol route after preliminary deletion provided by an embodiment of the present invention;

[0039] Figure 4 A schematic diagram of a modified inspection path provided by an embodiment of the present invention;

[0040] Figure 5 A schematic diagram of a final inspection path of a UAV provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the photovoltaic charging control method and system for a drone airport proposed by the present invention, its specific implementation, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0042] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0043] The specific scheme of the photovoltaic charging control method and system for an unmanned aerial vehicle airport provided by the present invention is described in detail below with reference to the accompanying drawings.

[0044] The embodiment of the present invention mainly analyzes the available power of the drone airport and the remaining power of the drones on that day to determine whether the inspection needs of all drones can be met; when the inspection needs cannot be met, some inspection paths with a high degree of replaceability of the drones to be charged are deleted, and the drones to be charged are re-determined based on the corrected inspection paths, and it is re-determined whether the inspection needs can be met; until the inspection needs are met, the deletion of inspection paths is stopped, the final inspection path is determined, power is allocated to the drones, and under the condition of limited power, effective inspections are carried out on the inspection area, thereby improving the effective utilization rate of electric energy of the photovoltaic power supply system.

[0045] See also Figure 1 , which shows a flow chart of a photovoltaic charging control method for a drone airport provided by an embodiment of the present invention, specifically comprising:

[0046] Step S1: Obtain the preset inspection route of each drone, the power consumption per inspection distance, the remaining power, and the power available at the drone airport on that day.

[0047] In order to effectively control the photovoltaic charging of the drone airport, we first obtain the preset inspection route of each drone, the power consumption per inspection distance, the remaining power and the power supply of the drone airport on that day to provide a data basis for analysis.

[0048] See also Figure 2 , which shows a schematic diagram of a preset inspection path of a drone provided by an embodiment of the present invention, Figure 2 Each line shape is a preset inspection path for a drone.

[0049] It should be noted that, in one embodiment of the present invention, an inspection is performed once a day, the preset inspection path of each drone is fixed, the final inspection path is included in the preset inspection path, all drones have the same configuration and function, and the power consumption per unit inspection distance is the same; the solar energy converted on the day is set for the inspection task of the day, and the LSTM (Long Short-Term Memory) prediction model is established through the historical sunshine duration, temperature changes and historical solar energy conversion efficiency. The conversion electric energy of the solar energy on the day is determined according to the sunshine duration and temperature changes on the day, and the remaining power in the energy storage device is combined to obtain the power supply of the drone airport on the day. Among them, the LSTM prediction model is already a prior art. In other embodiments of the present invention, the implementer can also supplement the factors of sunshine duration and temperature changes according to weather factors such as changes in light intensity, wind speed and wind direction in historical weather, and predict the weather conditions of the day, and finally predict the amount of electricity that can be converted on the day to obtain the power supply, which will not be repeated here.

[0050] In another embodiment of the present invention, the implementer may also stipulate that the electric energy converted from the solar energy on the first day is only used for inspections on the second day and thereafter. For example, if there is 50 kWh of electric energy remaining after the first day, a maximum of 50 kWh of electric energy will be used on the second day. The electric energy converted on the second day is only stored in the energy storage module for use in inspections on the third day and thereafter.

[0051] It should be noted that if there is extreme weather on the day, that is, weather conditions that do not meet the requirements for drone inspections, since the drone does not need to conduct inspections, there is no need to allocate the drone's power and it can be skipped directly.

[0052] It should be noted that, since the power consumption of the drone in non-inspection mode is relatively small, the present invention only considers the inspection power consumption on the inspection path, and does not consider other power consumption. The drone is set to start the inspection from the end of the inspection path closest to the airport, and can return along the inspection path or in a straight line when returning. The implementer can also reserve a specific energy storage space in the energy storage device. The power stored in the specific energy storage space is only used for the non-inspection power consumption of the drone. When obtaining the power available at the drone airport on that day, the power stored in the specific energy storage space is removed.

[0053] Step S2: Obtain the drones to be charged; based on the remaining power and available power of all the drones to be charged, combined with the length of the preset inspection routes and unit inspection distance of all the drones to be charged, determine whether the available power at the airport on that day can meet the inspection needs of all drones.

[0054] After obtaining the preset inspection route of the drone, the power consumption per inspection distance and the remaining power, it is easy to obtain the power required for the drone to complete the preset inspection route, and then compare it with the remaining power to obtain the drone to be charged.

[0055] As an example, when the product of the preset inspection path corresponding to the drone and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, the corresponding drone is determined to be a drone to be charged.

[0056] According to the length of the preset inspection path of all drones to be charged and the unit inspection distance, it is easy to obtain the amount of electricity required for the inspection. At the same time, according to the remaining power and available power of all drones to be charged, it is easy to obtain the total amount of electricity available for consumption. Therefore, according to the remaining power and available power of all drones to be charged, combined with the length of the preset inspection path of all drones to be charged and the unit inspection distance, it can be determined whether the available power of the airport on that day meets the inspection needs of all drones, providing a decision-making basis for whether to delete the inspection path in the future, and finally controlling the photovoltaic charging.

[0057] Preferably, in one embodiment of the present invention, the sum of the available power and the remaining power of all drones to be charged is taken as the total power;

[0058] The sum of the lengths of the preset inspection paths of all the drones to be charged and the power consumption per inspection distance is taken as the total power demand;

[0059] When the total power is less than the total power demand, it is determined that the power available on that day cannot meet the inspection needs of all drones.

[0060] Step S3: When it is determined that the power supply on that day cannot meet the inspection needs of all drones, select the preset inspection path of any drone to be charged as the target path; obtain the overall substitutability of the target path based on the intersection characteristics of the target path and other preset inspection paths; segment the preset inspection path at the intersection between the preset inspection paths to obtain a segmented path; select any segmented path in the target path as the target segmented path; obtain the local substitutability of the target segmented path based on the intersection angle and path length between the target segmented path and other intersecting segmented paths, combined with the corresponding overall substitutability; control the deletion of the target segmented path based on the local substitutability of the target segmented path, and obtain the corrected inspection path of each drone to be charged.

[0061] When it is determined that the power available on that day cannot meet the inspection needs of all drones, it is necessary to delete the preset inspection path of the drone to be charged to reduce the power consumed by the inspection; at the same time, considering the different distribution and intersection of the preset inspection paths, the degree of substitution is different, so the preset inspection path of any drone to be charged is selected as the target path, and the substitutability of the target path is analyzed.

[0062] Taking into account that the UAV has a certain inspection range when inspecting on the inspection path, which is similar to the certain watering range of a road sprinkler when operating, when the inspection path of the UAV intersects, there will be repeated inspection areas. Therefore, according to the intersection characteristics of the target path and other preset inspection paths, the overall degree of substitutability of the target path is obtained, and the substitutability of the target path is quantified from an overall perspective, so as to facilitate the subsequent priority deletion of paths with high substitutability, reduce the impact on the overall inspection area, improve the flexibility and adaptability of the inspection task, and improve the energy utilization rate of the photovoltaic charging system in the UAV airport.

[0063] Preferably, in one embodiment of the present invention, considering that the more intersections there are between the target path and other patrol paths, the higher the overlap between the patrol areas of the target path and other patrol paths, the more replaceable they are, and the number of intersections is positively correlated with the overall degree of replaceability; considering that the smaller the intersection angle of the two paths, the more overlapping the patrol areas, so the intersection angle is negatively correlated with the overall degree of replaceability;

[0064] Based on this, the number of intersections between the target path and other preset inspection paths is obtained;

[0065] Obtain the intersection angle of the target path and other preset inspection paths; the intersection angle is the minimum intersection angle of the intersection of the two inspection paths;

[0066] According to the number of intersections corresponding to the target path and the intersection angles of all intersections, the overall degree of substitutability of the target path is obtained.

[0067] As an example, the intersection angle is in degrees, and the calculation formula for the overall degree of substitutability includes:

[0068]

[0069] Where v represents the sequence number of the target path; y v represents the overall degree of substitutability of the vth target path; N v represents the number of intersections between the vth target path and other preset inspection paths; θ v,irepresents the intersection angle of the i-th intersection between the v-th target path and other preset inspection paths; sin() represents a sine function; c represents a preset positive parameter divided by zero, and in this example, c=0.1.

[0070] In the calculation formula of the overall degree of substitutability, the intersection angle is mapped by the sine function. Since the intersection angle is the angle of the minimum intersection angle at the intersection of two inspection paths, the intersection angle is greater than or equal to 0° and less than or equal to 90°. In this value range, θ v,i The larger the value, the greater the sin(θ v,i ) is larger, and then negative correlation mapping is performed by taking the inverse method to adjust the logical relationship, θ v,i The larger the value, the smaller the overlap of the inspection areas and the smaller the overall degree of substitutability. v In the molecular position, N v The larger it is, that is, the more intersections there are, the higher the overlap between the target path and the inspection area of ​​other inspection paths is, and the greater the overall degree of substitutability is.

[0071] In other embodiments of the present invention, the implementer may also use an exponential function exp(-x) with a natural constant e as the base to perform negative correlation mapping, such as Where x represents the independent variable.

[0072] Considering that directly deleting the entire target path may easily remove too many inspection paths at one time, which is not conducive to ensuring the completion of the inspection task, the preset inspection path is segmented at the intersection between the preset inspection paths to obtain segmented paths; any segmented path in the target path is selected as the target segmented path; and further analysis is performed from a local perspective, also considering that the substitutability of the target segmented path is related to the intersection angle, and considering that the substitutability of the target segmented path is also related to its own path length and the path lengths of other intersecting segmented paths, and the greater the overall substitutability of itself, the greater the substitutability of the target segmented path, so according to the intersection angle and path length between the target segmented path and other intersecting segmented paths, combined with the corresponding overall substitutability, the local substitutability of the target segmented path is obtained.

[0073] Preferably, in one embodiment of the present invention, considering that the target segmented path may intersect with multiple segmented paths belonging to other drones, for example, the target segmented path belongs to drone A, the path endpoints are A and B, the path endpoint A intersects with two segmented paths belonging to drone B, and the path endpoint B intersects with a segmented path belonging to drone C, so any segmented path that intersects with the target segmented path and belongs to other drones is first selected as the determination path, so as to facilitate analysis one by one;

[0074] Considering that the smaller the intersection angle between the determination path and the target segmented path is, the closer they are to parallelism, the easier it is for the determination path to cover the inspection area of ​​the target segmented path. At the same time, the longer the determination path is relative to the target segmented path, the greater the area coverage of the current determination path in the local area, the larger the range of the inspection area that may overlap in the target segmented path, the smaller the impact of the deletion of the target segmented path on the inspection task, and the stronger the substitutability. Based on this, the ratio of the length of the determination path to the length of the target segmented path is used as the replacement coefficient;

[0075] According to the intersection angle between the target segmented path and the determination path, the replacement coefficient and the overall degree of substitutability of the target path, the local substitutability coefficient of the target segmented path is obtained; the intersection angle is negatively correlated with the local substitutability coefficient; the replacement coefficient and the overall degree of substitutability are both positively correlated with the local substitutability coefficient; the intersection angle between the target segmented path and the determination path is the same as the intersection angle between the target path to which the target segmented path belongs and the preset inspection path to which the determination path belongs at the corresponding intersection;

[0076] The maximum value of the local substitutability coefficients of the target segmented path and all the determined paths is selected as the local substitutability degree of the target segmented path.

[0077] As an example, the calculation formula for the degree of local substitutability includes:

[0078]

[0079] Wherein, v represents the sequence number of the target path; k represents the sequence number of the segmented path of the target path; j represents the sequence number of the determination path of the target segmented path; t v,k,j represents the local substitutability coefficient of the kth target segment path of the vth target path and the jth decision path; y v represents the overall degree of substitutability of the vth target path; L j represents the path length of the jth decision path; L v,k represents the path length of the kth target segment path of the vth target path; represents the replacement coefficient of the kth target segment path of the vth target path and the jth decision path; θ v,k,j represents the intersection angle between the kth target segment path of the vth target path and the jth decision path; d represents a preset positive parameter divided by zero, in this example d = 0.05; softmax{} represents a softmax function; cos() represents a cosine function.

[0080] In the calculation formula of the local substitutability, the greater the overall substitutability, the stronger the substitutability from the overall analysis of the target path, and the greater the local substitutability; since the intersection angle between the target segmented path and the determination path is the same as the intersection angle between the target path to which the target segmented path belongs and the preset inspection path to which the determination path belongs at the corresponding intersection, the intersection angle between the target segmented path and the determination path is greater than or equal to 0° and less than or equal to 90°. In this value range, θ v,k,j The larger the cos(θ v,k,j ) is smaller, the greater the degree of local substitutability; since the intersection angle may be 90°, in order to avoid the intersection angle of 90° The term is meaningless, set the parameter d, adjust cos(θ v,k,j ) value range; the larger the replacement coefficient, the longer the determination path is relative to the target segment path, the larger the possible overlapping inspection area is, the smaller the impact of the deletion of the target segment path on the inspection task is, the stronger the substitutability is, and the greater the degree of local substitutability is.

[0081] In other embodiments of the present invention, the implementer may also use the sine function to perform negative correlation mapping to obtain the local substitutability, such as

[0082] It should be noted that when the selected target path does not have an intersection, the target path is the target segmented path, and the overall substitutability and local substitutability are both 0.

[0083] After evaluating the substitutability of the target segmented path from both local and overall perspectives, the local substitutability degree that characterizes the degree to which the target segmented path can be deleted is obtained. The deletion of the target segmented path can be controlled according to the local substitutability degree of the target segmented path, and the corrected inspection path of each drone to be charged is obtained, dynamically adapting to the power supply of the energy storage module.

[0084] Preferably, in one embodiment of the present invention, considering that the greater the degree of local substitutability, the more the corresponding segmented path can be deleted, when the degree of local substitutability is greater than a first preset threshold, the corresponding target segmented path is determined to be deleted; since isolated segmented paths may remain after the deletion, for the sake of continuity of the inspection task, the segmented paths farthest from the airport and isolated in the target path are deleted at the same time, and the remaining paths in the target path are used as the corrected inspection paths of the corresponding drones to be charged.

[0085] See also Figure 3 , which shows a schematic diagram of a patrol path after preliminary deletion provided by an embodiment of the present invention, Figure 3 The circle encloses the isolated segment farthest from the airport in the target path and needs to be deleted simultaneously; see Figure 4, which shows a schematic diagram of a modified inspection path provided by an embodiment of the present invention, Figure 4 Deleted Figure 3 The most isolated segment in the path that is farthest from the airport.

[0086] In another embodiment of the present invention, the implementer may also retain Figure 3 For the segmented path that is farthest from the airport and isolated, the corresponding drone will still fly along the preset inspection path when performing inspections, but the inspection mode will only be turned on on the reserved segmented path.

[0087] Step S4: According to the latest revised inspection path of the drone to be charged, a new drone to be charged is obtained again. When it is re-determined that the power supply on that day cannot meet the inspection needs of all drones, the revised inspection path of the new drone to be charged is obtained again, until it is determined that the power supply on that day can meet the inspection needs of all drones, and the final inspection path of each drone is obtained.

[0088] After the inspection path is deleted in step S3, the inspection energy consumption demand of the current drones to be charged is reduced. At this time, the remaining power of some of the current drones to be charged may have met the corresponding revised inspection path, so new drones to be charged are acquired based on the latest revised inspection path of the drones to be charged; step S2 is executed again based on the latest acquired drones to be charged to determine whether the available power at the airport on that day meets the inspection needs of all drones; when it is re-determined that the available power on that day cannot meet the inspection needs of all drones, step S3 is executed again, and on the basis of the current revised inspection path, deletion is performed again to acquire the revised inspection path of the new drones to be charged, and steps S2-S3 are executed repeatedly to gradually reduce the charging demand of all drones until it is determined that the available power on that day can meet the inspection needs of all drones. At this time, the power consumption demand of the final revised inspection path can be met, and the final inspection path of each drone is obtained.

[0089] For example, it is first determined that drones A and C are both drones to be charged, and the revised inspection paths of A and C are obtained through step S3. At this time, the remaining power of A can meet the current revised inspection path, but C is still not satisfied. At this time, C is re-determined as a new drone to be charged, and A removes the mark of the drone to be charged. Finally, the inspection path of A is the current revised inspection path, and C again participates in determining whether the power supply at the airport on that day can meet the inspection needs of all drones.

[0090] It should be noted that, in one embodiment of the present invention, when it is determined that the power supply on the day cannot meet the inspection needs of all drones, if the local substitutability of all the latest drones to be charged is less than or equal to the first preset threshold, or there is no intersection on the inspection path corresponding to all the latest drones to be charged, the execution condition of step S3 is not met, and the path cannot be deleted again in a cyclic manner using the method of step S3. At this time, considering that the shorter the segmented path of the latest drone to be charged, the smaller the impact on the overall inspection task after deletion, so the shortest segmented path on the inspection path corresponding to all the latest drones to be charged is deleted, and the segmented path farthest from the airport and isolated is deleted to obtain the corrected inspection path of each drone to be charged. As an example, the first preset threshold is 0.8.

[0091] Similarly, in another embodiment of the present invention, the implementer may also retain the isolated segment path farthest from the airport.

[0092] It should be noted that when the drones to be charged are obtained for the first time on the day, since the remaining power of the drones that are not determined to be to be charged can already meet the inspection requirements of the corresponding preset inspection path, the preset inspection path is directly used as the final inspection path.

[0093] See also Figure 5 , which shows a schematic diagram of a final inspection path of a drone provided by an embodiment of the present invention. Figure 2 , Figure 5 The inspection routes of the two drones were shortened to accommodate the power supply limitations of the energy storage modules.

[0094] Step S5: Allocate power to each drone based on the final inspection route, remaining power, power consumption per inspection distance, and available power of each drone.

[0095] After the final inspection route of each drone is finally determined, the charging needs of the drone can be obtained based on the remaining power of the final inspection route and the power consumption per unit inspection distance, the photovoltaic charging can be controlled, and the available power can be distributed to each drone to perform the inspection tasks of the day.

[0096] Preferably, in one embodiment of the present invention, the product of the length of the final inspection path of each latest drone to be charged and the power consumption per unit inspection distance is used as the final power requirement of each latest drone to be charged; and power is allocated to the drones according to the final power requirement of each latest drone to be charged.

[0097] It should be noted that, except for the latest drone to be charged, the final power demand of other drones is 0; the photovoltaic power generation module converts solar energy into electrical energy and transmits it to the energy storage module, and obtains the available power of the energy storage module on that day and the final power demand of each latest drone to be charged through the charging control module, and distributes the power; the stored electric energy is output at 220V and 50Hz through the inverter module to charge the latest drone to be charged.

[0098] It should be noted that the performance of the drone’s battery needs to be tested regularly, including capacity, voltage and health status, to ensure that the battery can provide the required power to complete the inspection mission.

[0099] An embodiment of the present invention also provides a photovoltaic charging control system for an unmanned aerial vehicle airport, the system comprising a memory, a processor and a computer program, wherein the memory is used to store the corresponding computer program, the processor is used to run the corresponding computer program, and when the computer program runs in the processor, it can implement a photovoltaic charging control method for an unmanned aerial vehicle airport described in steps S1-S5.

[0100] In summary, in order to solve the technical problem of intelligently controlling photovoltaic charging to ensure inspection effect, the present invention first obtains the preset inspection path, power consumption per inspection distance, remaining power and available power of the drone airport on the day for each drone; further cyclically obtains the drone to be charged, and determines whether the available power of the airport on the day meets the inspection needs of all drones; when it is determined that the available power on the day cannot meet the inspection needs of all drones, the local replaceability of the target segmented path is obtained; according to the local replaceability of the target segmented path, the deletion of the target segmented path is controlled, and the revised inspection path of each drone to be charged is obtained, until it is determined that the available power on the day can meet the inspection needs of all drones, and the final inspection path of each drone is obtained; finally, according to the final inspection path, remaining power, power consumption per inspection distance and available power of each drone, each drone is allocated power. When it is determined that the available power on the day is insufficient, the present invention analyzes the replaceability of the inspection path from the local and overall perspectives, deletes the inspection path, ensures that the inspection of key areas is not affected, improves the flexibility and adaptability of the inspection task, and improves the energy utilization rate of the photovoltaic charging system in the drone airport.

[0101] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0102] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A photovoltaic charging control method for a drone airport, characterized in that: The method comprises: Obtain the preset inspection route of each drone, the power consumption per inspection distance, the remaining power, and the power available at the drone airport on that day; Obtain the drones to be charged; determine whether the power supply at the airport on that day meets the inspection requirements of all drones based on the remaining power and the available power of all the drones to be charged, combined with the length of the preset inspection paths and the unit inspection distance of all the drones to be charged; When it is determined that the power supply on that day cannot meet the inspection needs of all drones, the preset inspection path of any drone to be charged is selected as the target path; the overall substitutability of the target path is obtained according to the intersection characteristics of the target path and other preset inspection paths; the preset inspection path is segmented at the intersection points between the preset inspection paths to obtain segmented paths; any segmented path in the target path is selected as the target segmented path; the local substitutability of the target segmented path is obtained according to the intersection angle and path length between the target segmented path and other intersecting segmented paths, combined with the corresponding overall substitutability; the deletion of the target segmented path is controlled according to the local substitutability of the target segmented path, and the revised inspection path of each drone to be charged is obtained; According to the latest revised inspection path of the drone to be charged, a new drone to be charged is obtained again. When it is re-determined that the power supply on that day cannot meet the inspection needs of all drones, the revised inspection path of the new drone to be charged is obtained again, until it is determined that the power supply on that day can meet the inspection needs of all drones, and the final inspection path of each drone is obtained; Power is allocated to each drone according to the final inspection path, the remaining power, the power consumption per inspection distance and the available power of each drone.

2. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for determining whether the power supply at the airport on that day meets the inspection requirements of all drones includes: The sum of the available power and the remaining power of all the drones to be charged is taken as the total power; The sum of the products of the lengths of the preset inspection paths of all the drones to be charged and the power consumption per unit inspection distance is taken as the total power demand; When the total power is less than the total power demand, it is determined that the available power on that day cannot meet all drone inspection needs.

3. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for obtaining the overall degree of substitutability includes: Obtaining the number of intersections between the target path and other preset inspection paths; Obtaining an intersection angle at the intersection of the target path and the other preset inspection paths; the intersection angle is the minimum intersection angle at the intersection of the two inspection paths; The overall degree of substitutability of the target path is obtained according to the number of intersections corresponding to the target path and the intersection angles at all intersections; the number of intersections is positively correlated with the overall degree of substitutability; and the intersection angle is negatively correlated with the overall degree of substitutability.

4. The photovoltaic charging control method for a drone airport according to claim 3 is characterized in that: The method for obtaining the local substitutability degree includes: Select any segmented path that intersects with the target segmented path and belongs to other UAVs as a determination path; use the ratio of the length of the determination path to the length of the target segmented path as a replacement coefficient; According to the intersection angle between the target segmented path and the determination path, the replacement coefficient and the overall degree of substitution of the target path, a local substitution coefficient of the target segmented path is obtained; the intersection angle is negatively correlated with the local substitution coefficient; the replacement coefficient and the overall degree of substitution are both positively correlated with the local substitution coefficient; the intersection angle between the target segmented path and the determination path is the same as the intersection angle between the target path to which the target segmented path belongs and the preset inspection path to which the determination path belongs at the corresponding intersection; The maximum value of the local substitutability coefficients of the target segment path and all the determination paths is selected as the local substitutability degree of the target segment path.

5. The photovoltaic charging control method for a drone airport according to claim 4 is characterized in that: The method of controlling the deletion of the target segmented path according to the local replaceability degree of the target segmented path to obtain the corrected inspection path of each of the unmanned aerial vehicles to be charged includes: When the local replaceability is greater than a first preset threshold, the corresponding target segmented path is determined to be deleted, and the segmented path farthest from the airport and isolated in the target path is deleted, and the remaining path in the target path is used as the corrected inspection path corresponding to the drone to be charged.

6. The photovoltaic charging control method for a drone airport according to claim 5 is characterized in that: When it is determined that the power supply on that day cannot meet the inspection needs of all drones, if the local substitutability of all the latest drones to be charged is less than or equal to the first preset threshold, or there is no intersection on the inspection path corresponding to all the latest drones to be charged, the shortest segmented path on the inspection path corresponding to all the latest drones to be charged is deleted, and the segmented path farthest from the airport and isolated is deleted to obtain the corrected inspection path of each drone to be charged.

7. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for distributing power to each drone includes: The product of the length of the final inspection path of each latest drone to be charged and the power consumption per unit inspection distance is used as the final power requirement of each latest drone to be charged; and power is allocated to the drones according to the final power requirement of each latest drone to be charged.

8. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for obtaining the drone to be charged includes: When the product of the preset inspection path corresponding to the drone and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, the corresponding drone is determined to be a drone to be charged.

9. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for reacquiring a new drone to be charged includes: If the product of the latest revised inspection path of the current drone to be charged and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, the corresponding drone is determined to be a new drone to be charged.

10. A photovoltaic charging control system for an unmanned aerial vehicle airport, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the photovoltaic charging control method for an unmanned aerial vehicle airport as described in any one of claims 1 to 9 are implemented.

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