Intelligent charging platform for unmanned aerial vehicle

Abstract

The invention relates to the technical field of unmanned aerial vehicles, in particular to an intelligent charging platform for an unmanned aerial vehicle, and the intelligent charging platform is characterized in that a first charging mechanism is adopted to charge the unmanned aerial vehicle, and the electric quantity variation in the charging process of the unmanned aerial vehicle is monitored in real time; whether the charging process of the unmanned aerial vehicle is qualified or not is preliminarily analyzed according to the electric quantity variable quantity, when the electric quantity variable quantity is small, the second charging mechanism is started, the first charging mechanism and the second charging mechanism conduct charging at the same time, and when one charging unit breaks down or charging efficiency is reduced, the other charging unit can still work continuously; the unmanned aerial vehicle can be normally charged, although the charging speed may be reduced, charging interruption cannot be caused, the situation that the use of the unmanned aerial vehicle is affected due to the fault of a single charging unit is avoided, and the charging efficiency can be improved by simultaneously using two charging units to charge different unmanned aerial vehicles in the scene of intensive operation of the unmanned aerial vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles, and in particular to an intelligent charging platform for unmanned aerial vehicles. Background Art

[0002] The drone charging platform can achieve fast charging, which greatly shortens the charging cycle of the drone and allows it to be put into the next mission more quickly. Especially in the case of frequent operations, it can significantly improve the use efficiency of the drone and increase its actual working time. The existing technology has realized the use of one charging pile to charge multiple drones by providing multiple wireless adaptive charging plates on each rotor drone charging pile, thereby improving the charging efficiency. However, if the charging unit fails or the charging efficiency is reduced during the drone charging process, the charging will be interrupted, affecting the charging efficiency.

[0003] Chinese patent application number: CN201510183601.5 discloses a rotor UAV charging pile and charging method, including a photovoltaic power generation panel, a support rod, a battery, a communication module, a bracket and a wireless adaptive charging plate, and also includes a horizontal shaft and a vertical shaft. The wireless adaptive charging plate is connected to the bracket through the vertical shaft, and the bracket is connected to the support rod through the horizontal shaft. Each rotor UAV charging pile has multiple wireless adaptive charging plates. Each platform reasonably utilizes the limited space near the support pile and provides more landing platforms to achieve the effect of charging multiple drones with one charging pile.

[0004] However, the prior art still has the following problems: If the charging unit fails or the charging efficiency decreases during the charging process of the drone, the charging will be interrupted, affecting the charging efficiency. Summary of the invention

[0005] To this end, the present invention provides an intelligent charging platform for a drone, so as to overcome the problem in the prior art that if a charging unit fails or the charging efficiency is reduced during the charging process of the drone, the charging will be interrupted, affecting the charging efficiency.

[0006] To achieve the above objectives, the present invention provides an intelligent charging platform for drones, including: shell; A loading unit, which is used to carry the drone and detect the pressure between the drone and the loading unit; A charging unit, which is disposed inside the loading unit and is used to charge the drone; Power supply unit, comprising: A first charging mechanism, which includes a photovoltaic panel and a power storage device, for outputting electric energy when the charging unit is activated; A second charging mechanism, which is used to output electric energy when the pressure between the loading unit and the drone reaches a predetermined value; A driving unit, which is disposed inside the loading unit and connected to the charging unit, and is used to drive the charging unit to move vertically; A data interaction unit, which is arranged inside the loading unit and connected to the power supply unit, and is used to establish data interaction with the drone when the power supply unit starts to charge the drone; A power detection unit, connected to the data interaction unit, for periodically detecting the power of the drone based on the interaction information; An analysis unit, which is respectively connected to the power supply unit, the data exchange unit and the power detection unit, and is used to analyze whether the charging process of the drone is qualified based on the change in the power of the drone measured by the power detection unit, and when it is initially determined that the charging process of the drone is unqualified, a secondary determination is made on whether the charging process of the drone is qualified based on the remaining power of the power storage device, or a processing method for the charging process of the drone is determined; A control unit is connected to the analysis unit and is used to adjust corresponding parameters according to the instructions of the analysis unit, and the parameters include: electromagnetic wave frequency and a first preset charging amount percentage.

[0007] Further, the analysis unit is used to analyze whether the charging process of the drone is qualified based on the change in the amount of power of the drone measured by the power detection unit, including: Determine the change in the drone's power within a predetermined time period, Calculate the ratio of the change in power to the total battery power of the drone to get the charging percentage. If the charging capacity percentage is greater than or equal to the first preset charging capacity percentage, the analysis unit determines that the charging process of the drone is qualified; If the charging capacity percentage is less than the first preset charging capacity percentage and greater than or equal to the second preset charging capacity percentage, the analysis unit preliminarily determines that the charging process of the drone is unqualified, and performs a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device; If the charging capacity percentage is less than the second preset charging capacity percentage, the analyzing unit determines that the charging process of the drone is unqualified, and determines a processing method for the charging process of the drone based on the charging capacity percentage.

[0008] Furthermore, the analysis unit performs a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device, including: If the remaining power is greater than or equal to the preset remaining power, the analysis unit determines that the charging process of the drone is unqualified, and determines a processing method for the charging process of the drone based on the charging capacity percentage; If the remaining power is less than the preset remaining power, the analyzing unit determines to start the second charging mechanism.

[0009] Furthermore, the analysis unit calculates the difference between the preset remaining power and the remaining power under the condition of determining to start the second charging mechanism, and determines the charging current ratio between the first charging mechanism and the second charging mechanism based on the difference, wherein the charging current ratio is negatively correlated with the difference.

[0010] Furthermore, the analysis unit determines a processing method for the charging process of the drone based on the charging capacity percentage, including: Calculating the difference between the second preset charging capacity percentage and the charging capacity percentage to obtain a percentage difference, If the percentage difference is less than or equal to a first preset percentage difference, the analysis unit determines to adjust the frequency of the electromagnetic wave of the charging coil; If the percentage difference is greater than the first preset percentage difference and less than or equal to the second preset percentage difference, the analysis unit determines to make a secondary determination on the processing method for the charging process of the drone based on the change of the charging amount in the historical data; If the percentage difference is greater than the second preset percentage difference, the analyzing unit determines to control the driving unit to start up to raise the charging unit.

[0011] Furthermore, the control unit is used to adjust the electromagnetic wave frequency of the charging coil based on the change in electrical charge when the analysis unit determines to adjust the electromagnetic wave frequency of the charging coil, wherein the increase in the electromagnetic wave frequency is negatively correlated with the change in electrical charge.

[0012] Furthermore, the analysis unit is used to make a secondary determination on the processing method of the charging process for the drone based on the change of the charging amount in the historical data, including: The analysis unit is used to draw a time-power change curve based on the change of charging capacity in the historical data, and analyze the reasons for the unqualified charging process of the drone based on the slope of the curve corresponding to the current time node in the curve. If the slope of the curve is less than or equal to the preset slope of the curve, the analysis unit determines that the reason why the charging process of the drone is unqualified is that the battery performance of the drone is unqualified; If the slope of the curve is greater than the preset slope of the curve, the analysis unit determines that the reason why the charging process of the drone is unqualified is that the charging power of the power supply unit is insufficient.

[0013] Furthermore, the control unit is used to adjust the first preset charge percentage based on the cumulative usage time of the battery of the drone when the battery performance of the drone is unqualified, wherein the reduction in the first preset charge percentage is positively correlated with the cumulative usage time.

[0014] Furthermore, the analysis unit is also used to monitor the pressure between the loading unit and the drone in real time when the driving unit is started to raise the charging unit.

[0015] Compared with the prior art, the beneficial effect of the present invention lies in that the first charging mechanism is first used to charge the drone, and the change in the amount of electricity during the charging process of the drone is monitored in real time. After charging for a predetermined time, a preliminary analysis is made as to whether the charging process of the drone is qualified based on the change in amount of electricity. When the change in amount of electricity is small, the second charging mechanism is started, and the first charging mechanism and the second charging mechanism are charged at the same time. When one charging unit fails or the charging efficiency is reduced, the other charging unit can continue to work to ensure that the drone can be charged normally. Although the charging speed may decrease, it will not cause charging interruption, thus avoiding the use of the drone being affected by the failure of a single charging unit. In scenarios where drones are intensively operated, two charging units are used simultaneously to charge different drones, which can improve the charging efficiency.

[0016] Furthermore, in the present invention, a preliminary analysis is first made as to whether the charging process of the drone is qualified based on the amount of power change. When the charging capacity percentage is between the first preset charging capacity percentage and the second preset charging capacity percentage, considering that the charging process is affected by various factors, the remaining power of the power storage device will affect the charging process, and too low a remaining power will cause the charging process to be interrupted. Therefore, a secondary judgment is made on the charging process of the drone based on the remaining power of the power storage device, thereby improving the control accuracy of the charging process for the drone.

[0017] Furthermore, the present invention takes into account that the health status of the drone's battery will have a great impact on the charging efficiency. A healthy battery can be charged at a higher efficiency, while an aged or damaged battery has a degraded performance of the chemical substances inside it, which may result in a slower charging speed, incomplete charging, etc., resulting in reduced charging efficiency. The present invention adjusts the first preset charging percentage according to the cumulative usage time of the drone's battery, thereby avoiding misjudgment caused by using a single judgment criterion to analyze charging processes in different states, thereby improving the accuracy of the analysis of the charging process. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a structural schematic diagram of an intelligent charging platform for drones; Figure 2 A flow chart for analyzing whether the charging process of a drone is qualified; Figure 3 A flowchart for secondary determination of whether the charging process of the drone is qualified; Figure 4 The figure is a flowchart for determining the processing method for the charging process of the drone. DETAILED DESCRIPTION

[0019] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0020] It should be pointed out that the data in this embodiment are obtained by comprehensive analysis and evaluation of the historical data of the system of the present invention in the six months before this determination and the corresponding historical determination results. It can be understood by those skilled in the art that the determination method of the system of the present invention for a single parameter mentioned above can be to select the value with the highest proportion as the preset standard parameter according to the data distribution, use weighted summation to use the obtained value as the preset standard parameter, substitute each historical data into a specific formula and use the value obtained by the formula as the preset standard parameter or other selection methods, as long as the system of the present invention can clearly define different specific situations in the single determination process through the obtained values.

[0021] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0022] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0023] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0024] See also Figure 1 As shown, it is a structural schematic diagram of an intelligent charging platform for drones.

[0025] The intelligent charging platform for a drone provided in this embodiment includes: Shell 1; A loading unit 2, which is used to carry the UAV and detect the pressure between the UAV and the loading unit; A charging unit 3, which is disposed inside the loading unit and is used to charge the drone; Power supply unit, comprising: A first charging mechanism 4, which includes a photovoltaic panel 5 and a power storage device (not shown in the figure), is used to output electric energy when the charging unit 3 is started; A second charging mechanism 6, which is used to output electric energy when the pressure between the loading unit 2 and the drone reaches a predetermined value; A driving unit 7, which is disposed inside the loading unit and connected to the charging unit, and is used to drive the charging unit 3 to move vertically; A data interaction unit, which is arranged inside the loading unit and connected to the power supply unit, and is used to establish data interaction with the drone when the power supply unit starts to charge the drone; A power detection unit, connected to the data interaction unit, for periodically detecting the power of the drone based on the interaction information; An analysis unit, which is respectively connected to the power supply unit, the data exchange unit and the power detection unit, and is used to analyze whether the charging process of the drone is qualified based on the change in the power of the drone measured by the power detection unit, and when it is initially determined that the charging process of the drone is unqualified, a secondary determination is made on whether the charging process of the drone is qualified based on the remaining power of the power storage device, or a processing method for the charging process of the drone is determined; A control unit is connected to the analysis unit and is used to adjust corresponding parameters according to the instructions of the analysis unit, and the parameters include: electromagnetic wave frequency and a first preset charging amount percentage.

[0026] Specifically, in this embodiment, a pressure sensor is provided on the surface of the loading unit, the first charging mechanism and the second charging mechanism are connected in parallel, and the main circuit is connected to the charging coil.

[0027] Specifically, in this embodiment, the specific structures of the data exchange unit, the power detection unit, the analysis unit and the control unit are not limited, and they can be composed of logical components, and the logical components include a field programmable processor, a computer and a microprocessor in the computer.

[0028] In the present invention, the first charging mechanism is first used to charge the drone, and the change in the amount of electricity during the charging process of the drone is monitored in real time. After charging for a predetermined time, a preliminary analysis is made as to whether the charging process of the drone is qualified based on the change in the amount of electricity. When the change in the amount of electricity is small, the second charging mechanism is started, and the first charging mechanism and the second charging mechanism are charged simultaneously. When one charging unit fails or the charging efficiency is reduced, the other charging unit can still continue to work to ensure that the drone can be charged normally. Although the charging speed may decrease, it will not cause charging interruption, thus avoiding the use of the drone being affected by the failure of a single charging unit. In the scenario of intensive drone operations, two charging units are used simultaneously to charge different drones, which can improve the charging efficiency.

[0029] See also Figure 2 As shown, it is a flow chart for analyzing whether the charging process of the drone is qualified.

[0030] Specifically, the analysis unit is used to analyze whether the charging process of the drone is qualified based on the change in the power of the drone measured by the power detection unit, including: Determine the change in the drone's power within a predetermined time period, Calculate the ratio of the change in power to the total battery power of the drone to get the charging percentage. If the charging capacity percentage is greater than or equal to the first preset charging capacity percentage, the analysis unit determines that the charging process of the drone is qualified; If the charging capacity percentage is less than the first preset charging capacity percentage and greater than or equal to the second preset charging capacity percentage, the analysis unit preliminarily determines that the charging process of the drone is unqualified, and performs a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device; If the charging capacity percentage is less than the second preset charging capacity percentage, the analyzing unit determines that the charging process of the drone is unqualified, and determines a processing method for the charging process of the drone based on the charging capacity percentage.

[0031] Specifically, in this embodiment, the first preset charging percentage and the second preset charging percentage are obtained in advance, the charging process data of several drones with qualified charging processes are obtained, the data of the change in the amount of power of the drones in the corresponding predetermined time period are extracted, and the charging percentages and the average charging percentages are solved respectively. The first preset charging percentage is 1.05 times the average charging percentage, and the second preset charging percentage is 0.85 times the average charging percentage.

[0032] In the present invention, whether the charging process of the drone is qualified is preliminarily analyzed based on the amount of power change. When the charging capacity percentage is between the first preset charging capacity percentage and the second preset charging capacity percentage, considering that the charging process is affected by various factors, the remaining power of the power storage device will affect the charging process, and too low remaining power will cause the charging process to be interrupted. Therefore, the charging process of the drone is secondary judged based on the remaining power of the power storage device, thereby improving the control accuracy of the charging process for the drone.

[0033] See also Figure 3 As shown, it is a flow chart for secondary determination of whether the charging process of the drone is qualified.

[0034] Specifically, the analysis unit performs a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device, including: If the remaining power is greater than or equal to the preset remaining power, the analysis unit determines that the charging process of the drone is unqualified, and determines a processing method for the charging process of the drone based on the charging capacity percentage; If the remaining power is less than the preset remaining power, the analyzing unit determines to start the second charging mechanism.

[0035] Specifically, in this embodiment, when it is determined to start the second charging mechanism, the first charging mechanism and the second charging mechanism charge the drone simultaneously.

[0036] Specifically, in this embodiment, the preset remaining power is 20% to 25% of the total power.

[0037] Specifically, the analysis unit calculates the difference between the preset remaining power and the remaining power under the condition of determining to start the second charging mechanism, and determines the charging current ratio of the first charging mechanism and the second charging mechanism based on the difference, wherein the charging current ratio is negatively correlated with the difference.

[0038] In this embodiment, optionally, The difference is compared with the first preset difference and the second preset difference, If the difference is less than or equal to the first preset difference, the charging current ratio is determined to be 0.4; If the difference is greater than the first preset difference and less than or equal to the second preset difference, determining the charging current ratio to be 0.3; If the difference is greater than the second preset difference, determining the charging current ratio to be 0.2; The first preset difference is 0.15 times the preset remaining power, and the second preset difference is 0.2 times the preset remaining power.

[0039] See also Figure 4As shown, it is a flow chart for determining the processing method for the charging process of the drone.

[0040] Specifically, the analysis unit determines a processing method for the charging process of the drone based on the charging percentage, including: Calculating the difference between the second preset charging capacity percentage and the charging capacity percentage to obtain a percentage difference, If the percentage difference is less than or equal to a first preset percentage difference, the analysis unit determines to adjust the frequency of the electromagnetic wave of the charging coil; If the percentage difference is greater than the first preset percentage difference and less than or equal to the second preset percentage difference, the analysis unit determines to make a secondary determination on the processing method for the charging process of the drone based on the change of the charging amount in the historical data; If the percentage difference is greater than the second preset percentage difference, the analyzing unit determines to control the driving unit to start up to raise the charging unit.

[0041] Specifically, in this embodiment, the first preset percentage difference is 0.2 times the second preset charging capacity percentage, and the second preset percentage difference is 0.3 times the second preset charging capacity percentage.

[0042] Specifically, the control unit is used to adjust the electromagnetic wave frequency of the charging coil based on the change in power when the analysis unit determines to adjust the electromagnetic wave frequency of the charging coil, wherein the increase in the electromagnetic wave frequency is negatively correlated with the change in power.

[0043] In this embodiment, optionally, The power change is compared with the first preset power change and the second preset power change. If the amount of change in power is less than or equal to the first preset amount of change in power, the frequency of the electromagnetic wave is adjusted to 1.25 times the initial electromagnetic wave frequency; If the amount of change in power is greater than the first preset amount of change in power and less than or equal to the second preset amount of change in power, adjusting the frequency of the electromagnetic wave to 1.2 times the initial electromagnetic wave frequency; If the amount of change in the amount of electricity is greater than the second preset amount of change in the amount of electricity, adjusting the frequency of the electromagnetic wave to 1.1 times the initial electromagnetic wave frequency; Among them, the first preset power change and the second preset power change are obtained in advance, and the charging process data of several drones with qualified charging processes are obtained, and the data of the power change of the drones in the corresponding predetermined time period are extracted to solve the average power change. The first preset power change is 0.95~1.05 times the average power change, and the second preset power change is 1.1~1.2 times the average power change.

[0044] Specifically, the analysis unit is used to make a secondary determination on the processing method of the charging process for the drone based on the change of the charging amount in the historical data, including: The analysis unit is used to draw a time-power change curve based on the change of charging capacity in the historical data, and analyze the reasons for the unqualified charging process of the drone based on the slope of the curve corresponding to the current time node in the curve. If the slope of the curve is less than or equal to the preset slope of the curve, the analysis unit determines that the reason why the charging process of the drone is unqualified is that the battery performance of the drone is unqualified; If the slope of the curve is greater than the preset slope of the curve, the analysis unit determines that the reason why the charging process of the drone is unqualified is that the charging power of the power supply unit is insufficient.

[0045] Specifically, in this embodiment, the slope of the preset curve is obtained by pre-measurement, and the charging process data of several drones with qualified charging processes are obtained, and the data of the change in the amount of power of the drones in the corresponding predetermined time period are extracted. The time-power change curves are plotted respectively, and the average value of the curve slope at each time node is solved to obtain the preset curve slope.

[0046] Specifically, the control unit is used to adjust the first preset charge percentage based on the cumulative usage time of the battery of the drone when the battery performance of the drone is unqualified, wherein the reduction in the first preset charge percentage is positively correlated with the cumulative usage time.

[0047] In this embodiment, optionally, The accumulated usage time is compared with the first preset accumulated usage time and the second preset accumulated usage time. If the accumulated usage time is less than or equal to the first preset accumulated usage time, the first preset charge capacity percentage is reduced to 0.98 times the initial first preset charge capacity percentage; If the accumulated usage time is greater than the first preset accumulated usage time and less than or equal to the second preset accumulated usage time, the first preset charge capacity percentage is reduced to 0.95 times the initial first preset charge capacity percentage; If the accumulated usage time is greater than the second preset accumulated usage time, reducing the first preset charge capacity percentage to 0.92 times the initial first preset charge capacity percentage; Among them, the adjusted first preset charging percentage is greater than the second preset charging percentage, and the best performance usage time of the battery model used by the drone is obtained based on big data. The first preset cumulative usage time is 1.15 times the usage time, and the second preset cumulative usage time is 1.2 times the usage time.

[0048] The present invention takes into account that the health status of the drone's battery will have a great impact on the charging efficiency. A healthy battery can be charged at a higher efficiency, while an aged or damaged battery has a degraded performance of the chemical substances inside, which may result in a slower charging speed, incomplete charging, etc., resulting in reduced charging efficiency. The present invention adjusts the first preset charging capacity percentage according to the cumulative usage time of the drone's battery, thereby avoiding misjudgment caused by analyzing the charging process in different states using a single judgment criterion, thereby improving the accuracy of the analysis of the charging process.

[0049] Specifically, the analysis unit is also used to monitor the pressure between the loading unit and the drone in real time when the driving unit is started to raise the charging unit.

[0050] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0051] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent charging platform for drones, characterized in that: include: shell; A loading unit, which is used to carry the drone and detect the pressure between the drone and the loading unit; A charging unit, which is disposed inside the loading unit and is used to charge the drone; Power supply unit, comprising: A first charging mechanism, which includes a photovoltaic panel and a power storage device, for outputting electric energy when the charging unit is activated; A second charging mechanism, which is used to output electric energy when the pressure between the loading unit and the drone reaches a predetermined value; A driving unit, which is disposed inside the loading unit and connected to the charging unit, and is used to drive the charging unit to move vertically; A data interaction unit, which is arranged inside the loading unit and connected to the power supply unit, and is used to establish data interaction with the drone when the power supply unit starts to charge the drone; A power detection unit, connected to the data interaction unit, for periodically detecting the power of the drone based on the interaction information; An analysis unit, which is respectively connected to the power supply unit, the data exchange unit and the power detection unit, and is used to analyze whether the charging process of the drone is qualified based on the change in the power of the drone measured by the power detection unit, and when it is initially determined that the charging process of the drone is unqualified, a secondary determination is made on whether the charging process of the drone is qualified based on the remaining power of the power storage device, or a processing method for the charging process of the drone is determined; A control unit is connected to the analysis unit and is used to adjust corresponding parameters according to the instructions of the analysis unit, and the parameters include: electromagnetic wave frequency and a first preset charging amount percentage.

2. The intelligent charging platform for drones according to claim 1, characterized in that: The analyzing unit is used to analyze whether the charging process of the drone is qualified based on the change in the amount of power of the drone measured by the power detection unit, including: Determine the change in the drone's power within a predetermined time period, Calculate the ratio of the change in power to the total battery power of the drone to get the charging percentage. If the charging capacity percentage is greater than or equal to the first preset charging capacity percentage, the analysis unit determines that the charging process of the drone is qualified; If the charging capacity percentage is less than the first preset charging capacity percentage and greater than or equal to the second preset charging capacity percentage, the analysis unit preliminarily determines that the charging process of the drone is unqualified, and performs a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device; If the charging capacity percentage is less than the second preset charging capacity percentage, the analyzing unit determines that the charging process of the drone is unqualified, and determines a processing method for the charging process of the drone based on the charging capacity percentage.

3. The intelligent charging platform for drones according to claim 1, characterized in that: The analysis unit performs a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device, including: If the remaining power is greater than or equal to the preset remaining power, the analysis unit determines that the charging process of the drone is unqualified, and determines a processing method for the charging process of the drone based on the charging capacity percentage; If the remaining power is less than the preset remaining power, the analyzing unit determines to start the second charging mechanism.

4. The intelligent charging platform for drones according to claim 3, characterized in that: The analysis unit calculates the difference between the preset remaining power and the remaining power under the condition of determining to start the second charging mechanism, and determines the charging current ratio between the first charging mechanism and the second charging mechanism based on the difference, wherein the charging current ratio is negatively correlated with the difference.

5. The intelligent charging platform for drones according to claim 2, characterized in that: The analysis unit determines a processing method for the charging process of the drone based on the charging percentage, including: Calculating the difference between the second preset charging capacity percentage and the charging capacity percentage to obtain a percentage difference, If the percentage difference is less than or equal to the first preset percentage difference, the analysis unit determines to adjust the frequency of the electromagnetic wave of the charging coil; If the percentage difference is greater than the first preset percentage difference and less than or equal to the second preset percentage difference, the analysis unit determines to make a secondary determination on the processing method for the charging process of the drone based on the change of the charging amount in the historical data; If the percentage difference is greater than the second preset percentage difference, the analyzing unit determines to control the driving unit to start up to raise the charging unit.

6. The intelligent charging platform for drones according to claim 5, characterized in that: The control unit is used to adjust the electromagnetic wave frequency of the charging coil based on the amount of charge change when the analysis unit determines to adjust the electromagnetic wave frequency of the charging coil, wherein the increase in the electromagnetic wave frequency is negatively correlated with the amount of charge change.

7. The intelligent charging platform for drones according to claim 5, characterized in that: The analysis unit is used to make a secondary determination on the processing method of the charging process for the drone based on the change of the charging amount in the historical data, including: The analysis unit is used to draw a time-power change curve based on the change of charging capacity in the historical data, and analyze the reasons for the unqualified charging process of the drone based on the slope of the curve corresponding to the current time node in the curve. If the slope of the curve is less than or equal to the preset slope of the curve, the analysis unit determines that the reason why the charging process of the drone is unqualified is that the battery performance of the drone is unqualified; If the slope of the curve is greater than the preset slope of the curve, the analysis unit determines that the reason why the charging process of the drone is unqualified is that the charging power of the power supply unit is insufficient.

8. The intelligent charging platform for drones according to claim 7, characterized in that: The control unit is used to adjust the first preset charge percentage based on the cumulative usage time of the battery of the drone when the battery performance of the drone is unqualified, wherein the reduction amount of the first preset charge percentage is positively correlated with the cumulative usage time.

9. The intelligent charging platform for drones according to claim 7, characterized in that: The analysis unit is also used to monitor the pressure between the loading unit and the drone in real time when the driving unit is started to raise the charging unit.

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