An intelligent charging platform for drones

Abstract

The present invention relates to the technical field of unmanned aerial vehicles, and particularly to an intelligent charging platform for unmanned aerial vehicles. In the present invention, a first charging mechanism is first used to charge the unmanned aerial vehicle, and the change in the amount of electricity during the charging process of the unmanned aerial vehicle is monitored in real time. After a predetermined charging time, it is preliminarily analyzed whether the charging process of the unmanned aerial vehicle is qualified according to 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 charge simultaneously. When a charging unit fails or the charging efficiency decreases, the other charging unit can still continue to work, ensuring that the unmanned aerial vehicle can be normally charged. Although the charging speed may decrease, it will not cause the charging to be interrupted, avoiding the influence on the use of the unmanned aerial vehicle due to the failure of a single charging unit. In the scenario of intensive operation of unmanned aerial vehicles, two charging units can be used simultaneously to charge different unmanned aerial vehicles, which can improve the charging efficiency.

Description

Technical Field

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

[0002] The unmanned aerial vehicle charging platform can achieve fast charging, greatly shortening the charging cycle of the unmanned aerial vehicle, enabling it to be put into the next mission faster. Especially in the case of frequent operations, it can significantly improve the usage efficiency of the unmanned aerial vehicle and increase its actual working duration. The prior art has realized charging multiple unmanned aerial vehicles with one charging pile by arranging multiple wireless adaptive charging boards on each rotor unmanned aerial vehicle charging pile, improving the charging efficiency. However, during the charging process of the unmanned aerial vehicle, if a charging unit fails or the charging efficiency decreases, it will cause charging interruption and affect the charging efficiency.

[0003] Chinese Patent Application No.: CN201510183601.5 discloses a rotor unmanned aerial vehicle charging pile and a charging method, including a photovoltaic power generation board, a support rod, a storage battery, a communication module, a bracket, and a wireless adaptive charging board. It also includes a horizontal rotating shaft and a vertical rotating shaft. The wireless adaptive charging board is connected to the bracket through the vertical rotating shaft, and the bracket is connected to the support rod through the horizontal rotating shaft. Each rotor unmanned aerial vehicle charging pile has multiple wireless adaptive charging boards. Each platform reasonably utilizes the limited space near the support pile, providing more landing platforms to achieve the effect of charging multiple unmanned aerial vehicles with one charging pile.

[0004] However, the prior art still has the following problems:

[0005] During the charging process of the unmanned aerial vehicle, if a charging unit fails or the charging efficiency decreases, it will cause charging interruption and affect the charging efficiency. Summary of the Invention

[0006] Therefore, the present invention provides an intelligent charging platform for unmanned aerial vehicles to overcome the problem that during the charging process of the unmanned aerial vehicle in the prior art, if a charging unit fails or the charging efficiency decreases, it will cause charging interruption and affect the charging efficiency.

[0007] To achieve the above object, the present invention provides an intelligent charging platform for unmanned aerial vehicles. The intelligent charging platform includes:

[0008] A housing;

[0009] A loading unit for carrying the unmanned aerial vehicle and detecting the pressure between the loading unit and the unmanned aerial vehicle;

[0010] A charging unit disposed inside the loading unit for charging the unmanned aerial vehicle;

[0011] A power supply unit, including:

[0012] The first charging mechanism, which includes a photovoltaic panel and a power storage device, is used to output electrical energy when the charging unit is started;

[0013] The second charging mechanism is used to output electrical energy when the pressure between the loading unit and the drone measured reaches a predetermined value;

[0014] The driving unit is arranged inside the loading unit and connected to the charging unit, and is used to drive the charging unit to move vertically;

[0015] The data interaction unit 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;

[0016] The battery level detection unit is connected to the data interaction unit, and is used to periodically detect the battery level of the drone based on the interaction information;

[0017] The analysis unit is respectively connected to the power supply unit, the data interaction unit and the battery level detection unit, and is used to analyze whether the charging process of the drone is qualified based on the change amount of the battery level of the drone measured by the battery level detection unit. 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;

[0018] The control unit is connected to the analysis unit, and is used to adjust the corresponding parameters according to the instructions of the analysis unit. The parameters include: electromagnetic wave frequency and the first preset charging percentage.

[0019] Further, the analysis unit is used to analyze whether the charging process of the drone is qualified based on the change amount of the battery level of the drone measured by the battery level detection unit, including:

[0020] Determine the change amount of the battery level of the drone within a predetermined time period,

[0021] Calculate the ratio of the change amount of the battery level to the total battery level of the drone to obtain the charging percentage,

[0022] If the charging percentage is greater than or equal to the first preset charging percentage, the analysis unit determines that the charging process of the drone is qualified;

[0023] If the charging percentage is less than the first preset charging percentage and greater than or equal to the second preset charging percentage, the analysis unit initially determines that the charging process of the drone is unqualified, and makes a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device;

[0024] If the percentage of the charged amount is less than the second preset charged amount percentage, the analysis unit determines that the charging process of the drone is unqualified, and determines the processing method for the charging process of the drone based on the percentage of the charged amount.

[0025] Further, the analysis unit makes a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device, including:

[0026] 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 the processing method for the charging process of the drone based on the percentage of the charged amount;

[0027] If the remaining power is less than the preset remaining power, the analysis unit determines to start the second charging mechanism.

[0028] Further, under the condition that the analysis unit determines to start the second charging mechanism, the analysis unit calculates the difference between the preset remaining power and the remaining power, and the analysis unit determines the charging current ratio between the first charging mechanism and the second charging mechanism based on the difference, where the charging current ratio is negatively correlated with the difference.

[0029] Further, the analysis unit determines the processing method for the charging process of the drone based on the percentage of the charged amount, including:

[0030] Calculate the difference between the second preset charged amount percentage and the percentage of the charged amount to obtain a percentage difference,

[0031] If the percentage difference is less than or equal to the first preset percentage difference, the analysis unit determines to adjust the electromagnetic wave frequency of the charging coil;

[0032] 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 situation of the charged amount in the historical data;

[0033] If the percentage difference is greater than the second preset percentage difference, the analysis unit determines to control the driving unit to start to raise the charging unit.

[0034] Further, the control unit is used to adjust the electromagnetic wave frequency of the charging coil based on the power change amount under the condition that the analysis unit determines to adjust the electromagnetic wave frequency of the charging coil, where the increase amount of the electromagnetic wave frequency is negatively correlated with the power change amount.

[0035] Further, the analysis unit is used to make a secondary determination on the processing method for the charging process of the drone based on the change situation of the charged amount in the historical data, including:

[0036] The analysis unit is used to draw a time - power change curve based on the change of the charging amount in the historical data, and analyze the reason for the unqualified charging process of the drone based on the curve slope corresponding to the current time node in the curve.

[0037] If the curve slope is less than or equal to the preset curve slope, the analysis unit determines that the reason for the unqualified charging process of the drone is the unqualified battery performance of the drone.

[0038] If the curve slope is greater than the preset curve slope, the analysis unit determines that the reason for the unqualified charging process of the drone is the insufficient charging power of the power supply unit.

[0039] Further, the control unit is used to adjust the first preset charging amount percentage based on the cumulative usage duration of the drone's battery under the condition that the battery performance of the drone is unqualified, wherein the decrease amount of the first preset charging amount percentage is positively correlated with the cumulative usage duration.

[0040] Further, 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.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows. In the present invention, the drone is first charged by the first charging mechanism, and the change of the power amount during the charging process of the drone is monitored in real time. After the charging for a predetermined time, it is preliminarily analyzed whether the charging process of the drone is qualified according to the change of the power amount. When the change of the power amount is small, the second charging mechanism is started, and the first charging mechanism and the second charging mechanism charge simultaneously. When a charging unit fails or the charging efficiency decreases, the other charging unit can still continue to work, ensuring that the drone can be normally charged. Although the charging speed may decrease, it will not cause the charging interruption, avoiding the influence on the use of the drone due to the failure of a single charging unit. In the scenario of intensive drone operations, two charging units are used to charge different drones simultaneously, which can improve the charging efficiency.

[0042] Further, in the present invention, it is first preliminarily analyzed whether the charging process of the drone is qualified according to the change of the power amount. When the charging amount percentage is between the first preset charging amount percentage and the second preset charging amount percentage, considering that the charging process is affected by various factors, the remaining power of the energy 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 re - judged according to the remaining power of the energy storage device, thereby improving the control accuracy of the charging process for the drone.

[0043] Furthermore, in the present invention, it is considered that the health status of the battery of the drone will have a great impact on the charging efficiency. A healthy battery can be charged at a higher efficiency, while for an aged or damaged battery, the performance of the internal chemical substances deteriorates, and situations such as slower charging speed and incomplete charging may occur, resulting in a decrease in charging efficiency. The present invention adjusts the first preset charging amount percentage according to the cumulative usage duration of the drone's battery, thereby avoiding misjudgment caused by analyzing the charging process in different states using a single determination criterion and improving the accuracy of the analysis of the charging process. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic structural diagram of an intelligent charging platform for a drone;

[0045] Figure 2 It is a determination flowchart for analyzing whether the charging process of the drone is qualified;

[0046] Figure 3 It is a determination flowchart for secondarily determining whether the charging process of the drone is qualified;

[0047] Figure 4 It is a determination flowchart for the processing method of the charging process of the drone. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] In order to make the objectives and advantages of the present invention clearer and more understandable, the present invention will be 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.

[0049] It should be noted that the data in this embodiment are all obtained through comprehensive analysis and evaluation of the historical data and corresponding historical determination results in the 6 months before this determination by the system described in the present invention. Those skilled in the art can understand that the determination method of the system described in the present invention for a single above-mentioned parameter can be to select the value with the highest proportion according to the data distribution as the preset standard parameter, use weighted summation to take the obtained value as the preset standard parameter, substitute each historical data into a specific formula and take the value obtained by using this formula as the preset standard parameter or other selection methods, as long as it satisfies that the system described in the present invention can clearly define different specific situations in a single determination process through the obtained values.

[0050] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0051] It should be noted that in the description of the present invention, the terms indicating the direction or positional relationship such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the direction or positional relationship shown in the drawings. This is only for 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 should not be construed as a limitation to the present invention.

[0052] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and defined, the terms "installation", "connection", and "connection" 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 directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0053] Please refer to Figure 1 shown, which is a schematic structural diagram of an intelligent charging platform for a drone.

[0054] The intelligent charging platform for a drone provided in this embodiment includes:

[0055] A housing 1;

[0056] A loading unit 2, which is used to carry the drone and detect the pressure between it and the drone;

[0057] A charging unit 3, which is arranged inside the loading unit and used to charge the drone;

[0058] A power supply unit, including:

[0059] A first charging mechanism 4, which includes a photovoltaic panel 5 and a power storage device (not shown in the figure), and is used to output electric energy when the charging unit 3 is started;

[0060] 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;

[0061] A driving unit 7, which is arranged inside the loading unit and connected to the charging unit, and is used to drive the charging unit 3 to move vertically;

[0062] 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;

[0063] A power detection unit, which is connected to the data interaction unit and is used to periodically detect the power of the drone based on the interaction information;

[0064] An analysis unit, which is respectively connected to the power supply unit, the data interaction unit and the power detection unit, is configured 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. When it is preliminarily determined that the charging process of the drone is unqualified, it will perform a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the energy storage device, or determine the processing method for the charging process of the drone.

[0065] A control unit, which is connected to the analysis unit, is configured to adjust corresponding parameters according to the instructions of the analysis unit. The parameters include: electromagnetic wave frequency and the first preset charging percentage.

[0066] 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.

[0067] Specifically, in this embodiment, the specific structures of the data interaction unit, the power detection unit, the analysis unit and the control unit are not limited. They can be composed of logic components, and the logic components include field programmable processors, computers and microprocessors in the computers.

[0068] In the present invention, the drone is first charged by the first charging mechanism, and the change in the power during the charging process of the drone is monitored in real time. After a predetermined charging time, it is preliminarily analyzed whether the charging process of the drone is qualified according to the change in the power. When the change in the power is small, the second charging mechanism is started, and the first charging mechanism and the second charging mechanism charge at the same time. When a charging unit fails or the charging efficiency decreases, the other charging unit can still continue to work, ensuring that the drone can be normally charged. Although the charging speed may decrease, it will not cause charging interruption, avoiding the influence on the use of the drone due to the failure of a single charging unit. In the scenario of intensive drone operations, two charging units can be used to charge different drones at the same time, which can improve the charging efficiency.

[0069] Please refer to Figure 2 as shown, which is a flowchart for determining whether the charging process of the drone is qualified.

[0070] Specifically, the analysis unit is configured 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:

[0071] Determine the change in the power of the drone within a predetermined time period.

[0072] Calculate the ratio of the change in the power to the total battery power of the drone to obtain the charging percentage.

[0073] If the percentage of the charged amount is greater than or equal to the first preset charged amount percentage, the analysis unit determines that the charging process of the drone is qualified;

[0074] If the percentage of the charged amount is less than the first preset charged amount percentage and greater than or equal to the second preset charged amount percentage, the analysis unit preliminarily determines that the charging process of the drone is unqualified, and makes a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device;

[0075] If the percentage of the charged amount is less than the second preset charged amount percentage, the analysis unit determines that the charging process of the drone is unqualified, and determines the processing method for the charging process of the drone based on the percentage of the charged amount.

[0076] Specifically, in this embodiment, the first preset charged amount percentage and the second preset charged amount percentage are obtained by pre-measurement. Obtain the charging process data of several drones with qualified charging processes, extract the data of the power change amount of the drones within the corresponding predetermined time period, solve the percentage of the charged amount respectively, and solve the average value of the percentage of the charged amount. The first preset charged amount percentage is 1.05 times the average value of the percentage of the charged amount, and the second preset charged amount percentage is 0.85 times the average value of the percentage of the charged amount.

[0077] In the present invention, first, it is preliminarily analyzed whether the charging process of the drone is qualified according to the power change amount. When the percentage of the charged amount is between the first preset charged amount percentage and the second preset charged amount 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, a secondary determination is made on the charging process of the drone according to the remaining power of the power storage device, thereby improving the control accuracy of the charging process of the drone.

[0078] Please refer to Figure 3 as shown, which is a flowchart for determining whether the charging process of the drone is qualified in the secondary determination.

[0079] Specifically, the analysis unit makes a secondary determination on whether the charging process of the drone is qualified based on the remaining power of the power storage device, including:

[0080] 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 the processing method for the charging process of the drone based on the percentage of the charged amount;

[0081] If the remaining power is less than the preset remaining power, the analysis unit determines to start the second charging mechanism.

[0082] Specifically, in this embodiment, when it is determined to activate the second charging mechanism, the first charging mechanism and the second charging mechanism charge the drone simultaneously.

[0083] Specifically, in this embodiment, the preset remaining power is 20% - 25% of the total power.

[0084] Specifically, under the condition that the analysis unit determines to activate the second charging mechanism, it calculates the difference between the preset remaining power and the remaining power. The analysis unit determines the charging current ratio of the first charging mechanism and the second charging mechanism based on this difference, where the charging current ratio is negatively correlated with the difference.

[0085] In this embodiment, optionally,

[0086] Compare the difference with a first preset difference and a second preset difference.

[0087] If the difference is less than or equal to the first preset difference, determine that the charging current ratio is 0.4;

[0088] If the difference is greater than the first preset difference and less than or equal to the second preset difference, determine that the charging current ratio is 0.3;

[0089] If the difference is greater than the second preset difference, determine that the charging current ratio is 0.2;

[0090] Wherein, 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.

[0091] Please refer to Figure 4 as shown, which is a decision flowchart for the processing method of the charging process of the drone.

[0092] Specifically, the analysis unit determines the processing method for the charging process of the drone based on the charging amount percentage, including:

[0093] Calculate the difference between the second preset charging amount percentage and the charging amount percentage to obtain a percentage difference.

[0094] If the percentage difference is less than or equal to the first preset percentage difference, the analysis unit determines to adjust the electromagnetic wave frequency of the charging coil;

[0095] 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 perform a secondary determination on the processing method for the charging process of the drone based on the change situation of the charging amount in the historical data;

[0096] If the percentage difference is greater than the second preset percentage difference, the analysis unit determines to control the driving unit to start to raise the charging unit.

[0097] Specifically, in this embodiment, the first preset percentage difference is 0.2 times the second preset charge percentage, and the second preset percentage difference is 0.3 times the second preset charge percentage.

[0098] Specifically, the control unit is used to adjust the electromagnetic wave frequency of the charging coil based on the power change amount under the condition that the analysis unit determines to adjust the electromagnetic wave frequency of the charging coil, wherein the increase amount of the electromagnetic wave frequency is negatively correlated with the power change amount.

[0099] In this embodiment, optionally,

[0100] Compare the power change amount with the first preset power change amount and the second preset power change amount.

[0101] If the power change amount is less than or equal to the first preset power change amount, adjust the electromagnetic wave frequency to 1.25 times the initial electromagnetic wave frequency;

[0102] If the power change amount is greater than the first preset power change amount and less than or equal to the second preset power change amount, adjust the electromagnetic wave frequency to 1.2 times the initial electromagnetic wave frequency;

[0103] If the power change amount is greater than the second preset power change amount, adjust the electromagnetic wave frequency to 1.1 times the initial electromagnetic wave frequency;

[0104] Among them, the first preset power change amount and the second preset power change amount are obtained by pre-measurement. Obtain the charging process data of several drones with qualified charging processes, extract the data of the power change amount of the drones within the corresponding predetermined time period, solve the average value of the power change amount, the first preset power change amount is 0.95 - 1.05 times the average value of the power change amount, and the second preset power change amount is 1.1 - 1.2 times the average value of the power change amount.

[0105] Specifically, the analysis unit is used to make a secondary determination on the processing method for the charging process of the drone based on the change situation of the charging amount in the historical data, including:

[0106] The analysis unit is used to draw a time-power change amount curve based on the change situation of the charging amount in the historical data, and analyze the reason for the unqualified charging process of the drone based on the curve slope corresponding to the current time node in the curve.

[0107] If the curve slope is less than or equal to the preset curve slope, the analysis unit determines that the reason for the unqualified charging process of the drone is that the battery performance of the drone is unqualified.

[0108] If the slope of the curve is greater than the preset curve slope, the analysis unit determines that the reason for the unqualified charging process of the drone is the insufficient charging power of the power supply unit.

[0109] Specifically, in this embodiment, the preset curve slope is obtained by pre-measurement. The charging process data of several drones with qualified charging processes are acquired, the data of the power change amount of the drones within the corresponding predetermined time period are extracted, the time-power change amount curves are respectively plotted, and the mean value of the curve slopes at each time node is solved to obtain the preset curve slope.

[0110] Specifically, the control unit is used to adjust the first preset charging amount percentage based on the cumulative usage duration of the battery of the drone under the condition that the battery performance of the drone is unqualified, where the reduction amount of the first preset charging amount percentage is positively correlated with the cumulative usage duration.

[0111] In this embodiment, optionally,

[0112] The cumulative usage duration is compared with the first preset cumulative usage duration and the second preset cumulative usage duration.

[0113] If the cumulative usage duration is less than or equal to the first preset cumulative usage duration, the first preset charging amount percentage is reduced to 0.98 times the initial first preset charging amount percentage;

[0114] If the cumulative usage duration is greater than the first preset cumulative usage duration and less than or equal to the second preset cumulative usage duration, the first preset charging amount percentage is reduced to 0.95 times the initial first preset charging amount percentage;

[0115] If the cumulative usage duration is greater than the second preset cumulative usage duration, the first preset charging amount percentage is reduced to 0.92 times the initial first preset charging amount percentage;

[0116] Among them, the adjusted first preset charging amount percentage is greater than the second preset charging amount percentage. Based on big data, the best usage duration of the battery of the drone model in use is obtained. The first preset cumulative usage duration is 1.15 times this usage duration, and the second preset cumulative usage duration is 1.2 times this usage duration.

[0117] In the present invention, it is considered that the health state of the battery of the drone has a great impact on the charging efficiency. A healthy battery can be charged at a relatively high efficiency, while for an aged or damaged battery, the performance of the internal chemical substances deteriorates, and situations such as a slower charging speed and incomplete charging may occur, resulting in a reduction in charging efficiency. The present invention adjusts the first preset charging amount percentage according to the cumulative usage duration of the drone's battery, thereby avoiding misjudgment caused by analyzing the charging process in different states using a single determination criterion and improving the accuracy of the analysis of the charging process.

[0118] Specifically, the analysis unit is further configured to, under the condition that the driving unit is started to raise the charging unit, monitor the pressure between the loading unit and the drone in real time.

[0119] So far, the technical solution of the present invention has been described in combination with the preferred embodiments shown in the 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.

[0120] The above are only the preferred embodiments of the present invention and are not used to limit the present invention; for those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, 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 connected to the analysis unit, for adjusting corresponding parameters according to the instructions of the analysis unit, the parameters including: electromagnetic wave frequency and a first preset charging amount percentage; 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; 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.

2. The intelligent charging platform for drones according to claim 1, 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.

3. The intelligent charging platform for drones according to claim 1, 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.

4. The intelligent charging platform for drones according to claim 3, 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.

5. The intelligent charging platform for drones according to claim 4, 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.

6. The intelligent charging platform for drones according to claim 5, 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.

7. The intelligent charging platform for drones according to claim 6, 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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