Control method and device of photovoltaic cleaning unmanned aerial vehicle and unmanned aerial vehicle

Abstract

The application discloses a photovoltaic cleaning unmanned aerial vehicle control method, device and unmanned aerial vehicle. The method comprises the following steps: acquiring the cleaning mode of the unmanned aerial vehicle, the cleaning progress of the lowest cleaning target, the flight power consumption coefficient and the distance to the nearest supply point in real time; obtaining the water quantity required for completing the lowest cleaning target as a dynamic water quantity threshold according to the cleaning mode and the cleaning progress; obtaining the electric quantity required for completing the lowest cleaning target as a first electric quantity according to the cleaning mode and the cleaning progress; determining the electric quantity required for returning to the nearest supply point as a second electric quantity according to the flight power consumption coefficient and the distance to the nearest supply point; obtaining a dynamic electric quantity threshold according to the first electric quantity and the second electric quantity; and judging whether the unmanned aerial vehicle needs to return to the supply point based on the dynamic electric quantity threshold and the dynamic water quantity threshold. The application improves the resource utilization rate of the unmanned aerial vehicle in the photovoltaic cleaning process.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic technology, and in particular to a control method, device, and drone for photovoltaic cleaning. Background Technology

[0002] With the development of photovoltaic technology, photovoltaic systems are being used more and more widely. During the use of photovoltaic systems, dust, bird droppings, oil stains, sand, and other contaminants accumulate on the surface of photovoltaic panels, reducing light transmittance and affecting photovoltaic power generation efficiency. Therefore, it is necessary to clean the photovoltaic panels. In existing technologies, drones equipped with water tanks are commonly used to clean photovoltaic panels, offering advantages such as high automation and good cleaning results. In practical applications, to prevent the drone from suddenly running out of water and power during operation, the cleaning task needs to be interrupted before the drone runs out of water and power, and it needs to return to the starting point to replenish water and power. After replenishment, the cleaning task continues. However, to ensure that the drone has enough power to return to the starting point, the set power threshold needs to be high enough, which may result in a certain degree of resource waste. Summary of the Invention

[0003] This invention provides a control method, device, and drone for photovoltaic cleaning, so as to improve the resource utilization rate of drones in the photovoltaic cleaning process.

[0004] According to one aspect of the present invention, a control method for a photovoltaic cleaning drone is provided, the method comprising: The system can acquire in real time the drone's cleaning mode, cleaning progress at the minimum cleaning target, flight power consumption coefficient, and distance to the nearest resupply point. Based on the cleaning mode and the cleaning progress, the amount of water required to complete the minimum cleaning target is obtained and used as a dynamic water volume threshold. Based on the cleaning mode and the cleaning progress, the amount of electricity required to complete the minimum cleaning target is obtained, which is used as the first amount of electricity. Based on the flight power consumption coefficient and the distance to the nearest resupply point, the amount of electricity required to return to the nearest resupply point is determined as the second amount of electricity; A dynamic power threshold is obtained based on the first power level and the second power level; Based on the dynamic power threshold and the dynamic water threshold, it is determined whether the drone needs to return to the resupply point.

[0005] Optionally, obtaining the water volume required to complete the minimum cleaning target based on the cleaning mode and the cleaning progress, and using it as a dynamic water volume threshold, includes: The water consumption coefficient is obtained based on the cleaning mode. Based on the water consumption coefficient and the cleaning progress, the amount of water required to complete the minimum cleaning target is obtained and used as a dynamic water volume threshold.

[0006] Optionally, obtaining the power required to complete the minimum cleaning target based on the cleaning mode and the cleaning progress includes: Based on the cleaning mode, the cleaning power consumption coefficient is obtained; Based on the cleaning power consumption coefficient and the cleaning progress, the amount of electricity required to complete the minimum cleaning target is obtained.

[0007] Optionally, before determining the amount of electricity required to return to the nearest resupply point based on the flight power consumption coefficient and the distance to the nearest resupply point, the method further includes: Real-time acquisition of the remaining water volume after the drone completes the minimum cleaning target; The flight power consumption coefficient is determined based on the remaining water volume; wherein the remaining water volume is positively correlated with the flight power consumption coefficient.

[0008] Optionally, the minimum cleaning objective is to clean the entire photovoltaic panel.

[0009] Optionally, after determining that the drone needs to return to the resupply point based on the dynamic power threshold and the dynamic water threshold, the method further includes: Based on the cleaning progress, if the minimum cleaning target is started but not completed, the drone is controlled to continue executing the minimum cleaning target until it is completed. Record the position of the currently completed minimum cleaning target as the breakpoint position; record the cleaning mode used by the currently completed minimum cleaning target as the cleaning mode before interruption. Control the drone to return to the resupply point.

[0010] Optionally, recording the position of the currently completed minimum cleaning target as the breakpoint position includes: Control the drone to fly to a safe gap between the edge of the currently cleaned photovoltaic panel and the edge of the next photovoltaic panel; The location of the safety gap is recorded as the breakpoint location.

[0011] Optionally, after controlling the drone to return to the resupply point, the method further includes: After resupplying the drone, control the drone to locate the breakpoint. The drone is controlled to automatically match the pre-interruption cleaning mode as the new minimum cleaning target cleaning mode.

[0012] Optionally, determining whether the drone needs to return to the resupply point based on the dynamic power threshold and the dynamic water threshold includes: The remaining battery power and water volume of the drone can be obtained in real time. If the remaining battery power is less than the dynamic battery power threshold, or the remaining water volume is less than the dynamic water volume threshold, a resupply command is triggered, and the drone needs to return to the resupply point.

[0013] Optionally, the cleaning progress of the drone can be acquired in real time, including: The coordinates of the starting cleaning point and the ending cleaning point on the photovoltaic panel are obtained, as well as the current coordinates of the drone in real time. The cleaning progress is obtained based on the coordinates of the starting cleaning point, the ending cleaning point, and the current coordinates.

[0014] Optionally, there are multiple supply points; real-time acquisition of the distance from the UAV to the nearest supply point includes: Based on the real-time acquired current coordinates of the UAV and the coordinates of each supply point, the straight-line distance between the UAV and each supply point is calculated. The minimum distance among all straight-line distances is selected as the distance for the UAV to reach the nearest supply point.

[0015] According to another aspect of the present invention, a control device for a photovoltaic cleaning drone is provided, the device comprising: The data acquisition module is used to acquire in real time the cleaning mode of the UAV, the cleaning progress of the minimum cleaning target, the flight power consumption coefficient, and the distance to the nearest supply point; The dynamic water volume threshold calculation module is used to obtain the water volume required to complete the minimum cleaning target based on the cleaning mode and the cleaning progress, and use it as the dynamic water volume threshold. The dynamic power threshold calculation module is used to obtain the power required to complete the minimum cleaning target based on the cleaning mode and the cleaning progress, as the first power; determine the power required to return to the nearest supply point based on the flight power consumption coefficient and the distance to the nearest supply point, as the second power; and obtain the dynamic power threshold based on the first power and the second power. The return-to-home determination module is used to determine whether the drone needs to return to the resupply point based on the dynamic power threshold and the dynamic water threshold.

[0016] According to another aspect of the present invention, a drone is provided, comprising: a drone main structure, a battery system, a cleaning system, and a control system, wherein the control system executes the control method for a photovoltaic cleaning drone as described in any embodiment of the present invention.

[0017] This invention, in its embodiments, calculates dynamic water volume thresholds and dynamic power thresholds in real time during the cleaning operation. The dynamic water volume threshold is the minimum water volume required to meet the minimum cleaning target, and the dynamic power threshold is the minimum power required to meet both the minimum cleaning target and the return-to-base resupply requirement. The return-to-base decision is based on both the minimum water volume threshold and the minimum power threshold. If either resource (water or power) is not met, a return-to-base command is triggered.

[0018] Compared to existing technologies that require a sufficiently high power threshold to ensure a drone has enough charge for return, this invention significantly reduces resource waste and improves resource utilization. For example, in this invention, when the drone is close to the nearest resupply point, the dynamically calculated power threshold is smaller, allowing more of the drone's power to be used for cleaning tasks. In contrast, existing technologies use a fixed and relatively large power threshold to ensure the drone returns from the furthest point from the resupply point. Even when the drone is close to the nearest resupply point, it will still initiate a return trip when the remaining power is just below the threshold, allowing the drone to still clean multiple photovoltaic panels. Therefore, compared to existing technologies, this invention reduces the frequency of drone return trips, thereby improving resource utilization during photovoltaic cleaning.

[0019] Furthermore, this embodiment of the invention also calculates a dynamic water volume threshold and combines it with a dynamic power consumption threshold to determine whether water and power resources are sufficient to achieve the minimum cleaning target. This setting avoids situations where the drone immediately returns before completing the minimum cleaning target. The minimum cleaning target could be, for example, cleaning the entire photovoltaic panel. Without the dynamic water volume and power consumption thresholds provided in this embodiment, there might be situations where the drone needs to return before cleaning the entire photovoltaic panel, and the drone's last position on the panel could be arbitrary. After resupply, the previously incompletely cleaned panels need to be cleaned again, and there might be issues with incomplete cleaning at the junctions. To achieve better cleaning results, the entire photovoltaic panel needs to be re-cleaned, resulting in a waste of water and power resources. This embodiment of the invention avoids this situation. If either water or power resources are insufficient to achieve the minimum cleaning target, a return operation is performed. After the drone resupply is complete, the next photovoltaic panel can be cleaned directly, eliminating the need to rework the incompletely cleaned panels, thereby improving resource utilization.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A schematic flowchart illustrating a control method for a photovoltaic cleaning drone provided in an embodiment of the present invention; Figure 2 A flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention; Figure 3 A flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention; Figure 4 A flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention; Figure 5 A flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention; Figure 6A flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of a control device for a photovoltaic cleaning drone provided in an embodiment of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] This invention provides a control method for a photovoltaic cleaning drone. The method can be executed by a control device for the photovoltaic cleaning drone, which can be implemented by software and / or hardware and can be configured in the drone.

[0026] Figure 1 This is a flowchart illustrating a control method for a photovoltaic cleaning drone provided in an embodiment of the present invention. See also... Figure 1 The control method for this photovoltaic cleaning drone includes the following steps: S110: Real-time acquisition of the drone's cleaning mode, cleaning progress of the minimum cleaning target, flight power consumption coefficient, and distance to the nearest resupply point; S120. Based on the cleaning mode and cleaning progress, obtain the water volume required to complete the minimum cleaning target, and use it as a dynamic water volume threshold. S130. Based on the cleaning mode and cleaning progress, obtain the power required to complete the minimum cleaning target, and use it as the first power. S140. Determine the amount of electricity required to return to the nearest resupply point based on the flight power consumption coefficient and the distance to the nearest resupply point, and use this as the second amount of electricity. S150. Obtain the dynamic power threshold based on the first power level and the second power level; S160. Based on the dynamic power threshold and dynamic water threshold, determine whether the drone needs to return to the resupply point; if so, control the drone to return to the resupply point; otherwise, return to S110.

[0027] Different cleaning modes result in variations in parameters such as water flow rate and pressure of the nozzles used on the drone for cleaning photovoltaic panels, leading to different rates of water and power consumption. For example, the cleaning modes include a high-pressure mode and a low-pressure mode. In high-pressure mode, the nozzle's water pressure is higher, and the motor controlling the water pressure has higher power, resulting in higher water and power consumption and a stronger cleaning intensity, suitable for cleaning heavily soiled photovoltaic panels. In low-pressure mode, the nozzle's water pressure is lower, and the motor controlling the water pressure has lower power, resulting in lower water and power consumption and a weaker cleaning intensity, suitable for cleaning less soiled photovoltaic panels. Optionally, in other embodiments, the cleaning modes may also include a medium-pressure mode, a slightly lower-pressure mode, a slightly higher-pressure mode, and a water-saving mode. In practical applications, the number of cleaning modes can be adjusted as needed.

[0028] The minimum cleaning target refers to the minimum cleaning task that needs to be completed before the drone returns to the resupply point. For example, the minimum cleaning target is to complete the cleaning of the photovoltaic panel currently being cleaned; or, the minimum cleaning target is to complete the cleaning of two photovoltaic panels; or, the minimum cleaning target is to complete the cleaning of half a photovoltaic panel; or, the minimum cleaning target is empty or 0, indicating that no minimum cleaning target is set.

[0029] Cleaning progress refers to how much work has been completed or how much work remains relative to the minimum cleaning target. For example, it can be expressed as a percentage or a decimal; for instance, if half of the minimum cleaning target has been completed, the cleaning progress is 50% or 0.5. The slower the cleaning progress, the more water and electricity are required; the faster the cleaning progress, the less water and electricity are required.

[0030] This invention utilizes the different cleaning modes and cleaning progress, which result in different amounts of water and electricity required, to calculate in real time the amount of water required to complete the minimum cleaning target, referred to as the water required for cleaning; and to calculate in real time the amount of electricity required to complete the minimum cleaning target, referred to as the electricity required for cleaning or the first electricity.

[0031] No water is consumed during the drone's return flight, so a dynamic water volume threshold is set for the water required for cleaning.

[0032] The flight power consumption coefficient refers to the power consumption intensity of a drone during its return flight. For example, the flight power consumption coefficient can be expressed as the power consumption required for 1 kilometer; or, the flight power consumption coefficient can also be expressed as the percentage of battery power required for 1 kilometer, etc.

[0033] The distance to the nearest supply point refers to the number of supply points set up for the photovoltaic panel cleaning task. These can be one, two, or more. When there is only one supply point, it is always the closest supply point to the drone. When there are two or more supply points, the nearest supply point changes dynamically. Regardless of the number of supply points, because the drone is always in flight, its distance to the nearest supply point changes dynamically, and therefore the power required for return also changes dynamically.

[0034] This invention utilizes the varying power consumption coefficients of flight and the distance to the nearest resupply point to calculate the required power in real time for returning to the nearest resupply point; this is referred to as the return-to-base power requirement or the second power requirement. Combining the power required for cleaning (i.e., the first power requirement) and the return-to-base power requirement (i.e., the second power requirement) yields a dynamic power threshold.

[0035] This invention, in its embodiments, calculates dynamic water volume thresholds and dynamic power thresholds in real time during the cleaning operation. The dynamic water volume threshold is the minimum water volume required to meet the minimum cleaning target, and the dynamic power threshold is the minimum power required to meet both the minimum cleaning target and the return-to-base resupply requirement. The return-to-base decision is based on both the minimum water volume threshold and the minimum power threshold. If either resource (water or power) is not met, a return-to-base command is triggered.

[0036] Compared to existing technologies that require a sufficiently high power threshold to ensure a drone has enough charge for return, this invention significantly reduces resource waste and improves resource utilization. For example, in this invention, when the drone is close to the nearest resupply point, the dynamically calculated power threshold is smaller, allowing more of the drone's power to be used for cleaning tasks. In contrast, existing technologies use a fixed and relatively large power threshold to ensure the drone returns from the furthest point from the resupply point. Even when the drone is close to the nearest resupply point, it will still initiate a return trip when the remaining power is just below the threshold, allowing the drone to still clean multiple photovoltaic panels. Therefore, compared to existing technologies, this invention reduces the frequency of drone return trips, thereby improving resource utilization during photovoltaic cleaning.

[0037] Furthermore, this embodiment of the invention also calculates a dynamic water volume threshold and combines it with a dynamic power consumption threshold to determine whether water and power resources are sufficient to achieve the minimum cleaning target. This setting avoids situations where the drone immediately returns before completing the minimum cleaning target. The minimum cleaning target could be, for example, cleaning the entire photovoltaic panel. Without the dynamic water volume and power consumption thresholds provided in this embodiment, there might be situations where the drone needs to return before cleaning the entire photovoltaic panel, and the drone's last position on the panel could be arbitrary. After resupply, the previously incompletely cleaned panels need to be cleaned again, and there might be issues with incomplete cleaning at the junctions. To achieve better cleaning results, the entire photovoltaic panel needs to be re-cleaned, resulting in a waste of water and power resources. This embodiment of the invention avoids this situation. If either water or power resources are insufficient to achieve the minimum cleaning target, a return operation is performed. After the drone resupply is complete, the next photovoltaic panel can be cleaned directly, eliminating the need to rework the incompletely cleaned panels, thereby improving resource utilization.

[0038] Based on the above embodiments, the present invention further specifies the specific implementation method of S120, which involves obtaining the amount of water required to complete the minimum cleaning target according to the cleaning mode, the minimum cleaning target, and the cleaning progress.

[0039] Figure 2 A schematic flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention. See also... Figure 2 In one embodiment, optionally, S120, based on the cleaning mode and cleaning progress, the amount of water required to complete the minimum cleaning target is obtained and used as a dynamic water volume threshold, specifically including the following steps: S121. Obtain the water consumption coefficient based on the cleaning mode; S122. Based on the water consumption coefficient and cleaning progress, obtain the amount of water required to complete the minimum cleaning target, and use it as the dynamic water volume threshold.

[0040] For example, the cleaning modes include a high-pressure mode and a low-pressure mode. In the high-pressure mode, the water pressure of the nozzle is higher, so the water consumption is higher. For example, the water consumption coefficient KW=1.2. In the low-pressure mode, the water pressure of the nozzle is lower, so the water consumption is lower. For example, the low-pressure mode is the base mode, and the water consumption coefficient KW=1.0.

[0041] For example, cleaning progress is the amount or percentage of cleaning work completed relative to a minimum cleaning target. For instance, S represents the percentage of work completed, and the remaining percentage is (1-S). The amount of water W required to complete the minimum cleaning target is also considered. 需=(1-S)·A·KW, where A represents the total water volume required to complete the entire minimum cleaning target in the baseline mode.

[0042] The embodiments of the present invention can obtain the water consumption coefficient based on the cleaning mode, and further combine it with the cleaning progress to obtain the water volume required to complete the minimum cleaning target. In the entire calculation process, the actual working conditions of the current drone operation are fully considered, which improves the accuracy of the dynamic water volume threshold.

[0043] Figure 3 A schematic flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention. See also... Figure 3 In one embodiment, optionally, S130, based on the cleaning mode and cleaning progress, the amount of electricity required to complete the minimum cleaning target is obtained as the first amount of electricity, specifically including the following steps: S131. Obtain the cleaning power consumption coefficient according to the cleaning mode; S132. Based on the cleaning power consumption coefficient and cleaning progress, obtain the power required to complete the minimum cleaning target, and use it as the first power.

[0044] For example, the cleaning modes include a high-pressure mode and a low-pressure mode. In the high-pressure mode, the motor used to control the water pressure of the nozzle has a higher power, so the power consumption is higher. For example, the cleaning power consumption coefficient KE=1.2. In the low-pressure mode, the motor used to control the water pressure of the nozzle has a lower power, so the power consumption is lower. For example, the low-pressure mode is the base mode, and the cleaning power consumption coefficient KE=1.0.

[0045] For example, cleaning progress refers to the amount or percentage of cleaning tasks completed relative to a minimum cleaning target. For instance, S represents the percentage of tasks completed, and the remaining percentage is (1-S). The electricity E required to complete the minimum cleaning target is also considered. 需 =(1-S)·B·KE, where B represents the total power required to complete the entire minimum cleaning target in the baseline mode.

[0046] The embodiments of the present invention can obtain the cleaning power consumption coefficient based on the cleaning mode, and further combine the cleaning progress to obtain the power required to complete the minimum cleaning target. In the entire calculation process, the actual working conditions of the current drone operation are fully considered, which improves the accuracy of the dynamic power threshold.

[0047] Figure 4 A schematic flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention. See also... Figure 4 In one embodiment, optionally, before S140, determining the amount of electricity required to return to the nearest resupply point based on the flight power consumption coefficient and the distance to the nearest resupply point, the method further includes: S170: Real-time acquisition of the remaining water volume after the drone completes the minimum cleaning target; S180. Determine the flight power consumption coefficient based on the remaining water volume; whereby the remaining water volume is positively correlated with the flight power consumption coefficient.

[0048] If the drone is forced to return to base due to insufficient battery power, the impact of remaining water on power consumption should also be considered during the return process. For example, the remaining water volume after the drone completes the minimum cleaning target can be obtained by subtracting the current remaining water volume from the water volume required to complete the minimum cleaning target. The more water remaining, the more power the drone needs to return to base, resulting in a higher power consumption coefficient; conversely, the less water remaining, the less power the drone needs to return to base, resulting in a lower power consumption coefficient.

[0049] Furthermore, based on the flight power consumption coefficient and the distance to the nearest resupply point, the amount of electricity required to return to the nearest resupply point is determined. For example, the amount of electricity E required for the drone to return is... 返 =D·M, where D represents the distance from the drone's position when it completes the minimum cleaning target to the nearest resupply point; M represents the flight power consumption coefficient, that is, the power consumption required to fly 1 kilometer.

[0050] The embodiments of the present invention obtain a dynamically changing flight power consumption coefficient based on the remaining water volume, and further combine the dynamically changing flight power consumption coefficient to obtain the power required for the drone to return after completing the minimum cleaning target. In the entire calculation process, the actual working conditions of the current drone operation are fully considered, which improves the accuracy of the dynamic power threshold.

[0051] It should be noted that the above embodiments only exemplify how different cleaning modes affect the cleaning power consumption coefficient. It is understood that the drone also consumes power to maintain flight during the cleaning task; therefore, the cleaning power consumption coefficient also includes the power required to maintain flight. However, in the aforementioned embodiments, it is assumed that only different cleaning modes affect the cleaning power consumption coefficient.

[0052] In another embodiment, optionally, when executing S130 and obtaining the power required to complete the minimum cleaning target based on the cleaning mode and cleaning progress, as the first power requirement, the influence of the remaining water in the tank on the drone's power consumption can also be considered when calculating the power required to complete the minimum cleaning target. That is, the remaining water in the tank also affects the cleaning power consumption coefficient, which will be explained in detail below.

[0053] Figure 5 A schematic flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention. See also... Figure 5 130. Based on the cleaning mode and cleaning progress, obtain the power required to complete the minimum cleaning target, which is used as the first power. This includes the following steps: S133. Based on the cleaning mode and the remaining water volume at the current moment, obtain the dynamically changing cleaning power consumption coefficient. S134. Based on the dynamically changing cleaning power consumption coefficient and cleaning progress, obtain the power required to complete the minimum cleaning target, and use it as the first power.

[0054] There are multiple cleaning modes. For example, the water pressure from the nozzles varies depending on the cleaning mode. A higher power motor controlling the water pressure results in higher power and water consumption for the cleaning system; conversely, a lower power motor results in lower power and water consumption. Specifically, when water consumption is rapid, the remaining water in the drone's tank decreases quickly, resulting in lower power consumption for the drone in achieving the minimum cleaning target. Conversely, when water consumption is slow, the remaining water in the drone's tank decreases slowly, resulting in higher power consumption for the drone in achieving the minimum cleaning target.

[0055] For example, the amount of electricity E required to achieve the minimum cleaning target 需 =∫[(1-S)·B·KE]dt, where S represents the percentage of the task that has been completed; B represents the total amount of electricity required to complete the entire minimum cleaning target in the baseline mode; KE changes dynamically as the task is completed; the lower limit of integration is 0, and the upper limit of integration is the time required to complete the minimum cleaning target.

[0056] The embodiments of the present invention can obtain the cleaning power consumption coefficient according to the cleaning mode. The cleaning power consumption coefficient is jointly determined by the power consumption of the cleaning system and the power consumption required for the drone to maintain flight. Furthermore, the power required to complete the minimum cleaning target is obtained by combining the cleaning progress. In the entire calculation process, the actual working conditions of the current drone operation are fully considered, which improves the accuracy of the dynamic power threshold.

[0057] Figure 6 A schematic flowchart illustrating another control method for a photovoltaic cleaning drone provided in an embodiment of the present invention. See also... Figure 6 Based on the above embodiments, optionally, after determining that the drone needs to return to the resupply point based on dynamic power thresholds and dynamic water thresholds, the method further includes: S190. Determine if 0 < S < 1; if yes, execute S1A0; otherwise, execute S1C0. S1A0: Control the drone to continue performing the minimum cleaning target until the minimum cleaning target is completed; S1B0: Record the position of the lowest completed cleaning target as the breakpoint position; record the cleaning mode used by the lowest completed cleaning target as the cleaning mode before the interruption. S1C0 controls the drone to return to the resupply point.

[0058] The system determines the cleaning progress based on a value S. If 0 < S < 1, it indicates that the minimum cleaning target has been initiated but not yet completed. For example, the minimum cleaning target is to clean the entire photovoltaic panel; 0 < S < 1 means that only a portion of the panel has been cleaned. If the drone then returns directly, its final position on the panel could be anywhere on the panel. After resupply, the previously incomplete panel needs to be cleaned again, and incomplete cleaning at the junctions can occur. To achieve better cleaning, the entire panel needs to be cleaned again, wasting water and electricity. This embodiment of the invention sets the drone to continue executing the minimum cleaning target until it is completed, avoiding the situation where only half of the panel is cleaned. After the drone completes cleaning, returns, and resupply, it directly cleans the next panel, eliminating the need to rework incomplete panels and improving resource utilization.

[0059] S=0 indicates that the photovoltaic panel has not yet started cleaning, and S=1 indicates that the photovoltaic panel has been cleaned. At this time, according to the dynamic water and power thresholds of this embodiment of the invention, it has been determined that the current power and / or water volume of the drone is insufficient to clean a complete photovoltaic panel. If cleaning of the photovoltaic panel continues, the panel will be forced to return after being partially cleaned. This embodiment of the invention sets the drone to return to the resupply point immediately, which can avoid the situation where the photovoltaic panel is only half-cleaned. After the drone resupply is completed, the next photovoltaic panel can be cleaned directly without reworking the uncleaned photovoltaic panel, thereby improving resource utilization.

[0060] In the above embodiments, after determining that the drone needs to return to the resupply point based on the dynamic water volume threshold and the dynamic power threshold, and judging that 0 < S < 1, but still continuing to complete the current photovoltaic panel cleaning task, will the drone be unable to return to the resupply point due to power depletion? It is understandable that before the current photovoltaic panel is cleaned, the dynamic water volume threshold and the dynamic power threshold determine that the drone's current power and water volume are sufficient to clean a complete photovoltaic panel. In actual execution, due to uncontrollable factors (e.g., increased power consumption due to the drone traveling against the wind), it may be determined that the drone cannot clean a complete photovoltaic panel during the cleaning process. On the one hand, it can be determined that under the current circumstances, the drone's remaining water volume or remaining power is not much less than the dynamic water volume threshold, and generally, it can still support the drone's return after cleaning the current photovoltaic panel. On the other hand, the photovoltaic panel is relatively small, for example, its length is 1m to 3m. Compared to the drone's battery capacity, the power required for the drone to clean a photovoltaic panel is relatively small, and generally, it can still support the drone's return after cleaning the current photovoltaic panel.

[0061] Furthermore, in this embodiment of the invention, before controlling the drone to return to base, breakpoint information is recorded. This breakpoint information specifically includes: the location of the lowest completed cleaning target, as the breakpoint location; and the cleaning mode used by the lowest completed cleaning target, as the cleaning mode before the interruption. This setting facilitates the ability to recall the breakpoint information, locate the breakpoint location, and automatically match the cleaning mode before the interruption to continue the cleaning task after the drone is resupplyed.

[0062] Optionally, the breakpoint information may also include the photovoltaic panel number, row number, column number, cleaning progress, remaining power, and remaining water volume. In practical applications, the information to be recorded can be set as needed.

[0063] Based on the above embodiments, optionally, the position of the lowest cleaning target currently completed is recorded as the breakpoint position, including: controlling the drone to fly to the safety gap between the edge of the currently cleaned photovoltaic panel and the edge of the next photovoltaic panel; and recording the position of the safety gap as the breakpoint position.

[0064] The safety gap at the edge of the photovoltaic panel is a pre-reserved safety gap on the outer side of the photovoltaic panel frame, meaning there is a certain distance between two photovoltaic panels. The drone flies to the position between the two photovoltaic panels and records this position as the breakpoint. While the drone is flying to this position, it continues to clean the photovoltaic panels until it returns to base. This setup ensures that the drone completes cleaning the previous photovoltaic panel, and after resupplying, it returns to the position between the two panels to clean the next one, thus avoiding repeated cleaning of the photovoltaic panel at the breakpoint.

[0065] Based on the above embodiments, optionally, after controlling the drone to return to the resupply point, the method further includes: after resupplying the drone, controlling the drone to locate the breakpoint; and controlling the drone to automatically match the cleaning mode before the interruption as the cleaning mode for executing the new minimum cleaning target. Controlling the drone to locate the breakpoint helps avoid missing or re-cleaning the photovoltaic panels. Controlling the drone to automatically match the cleaning mode before the interruption as the cleaning mode for executing the new minimum cleaning target enables the drone to automatically match the operating parameters before the interruption, ensuring consistent cleaning results before and after the interruption. Therefore, the embodiments of the present invention improve the adaptability of short-point continuation cleaning, achieving a breakpoint continuation cleaning effect with precise continuation cleaning location and consistent cleaning results.

[0066] Based on the above embodiments, optionally, a determination is made on whether the drone needs to return to the resupply point based on a dynamic power threshold and a dynamic water threshold, including: real-time acquisition of the drone's remaining power and remaining water; if the remaining power is less than the dynamic power threshold or the remaining water is less than the dynamic water threshold, a resupply command is triggered, and the drone needs to return to the resupply point.

[0067] For example, let E represent remaining electricity and W represent remaining water. The dynamic electricity threshold is abbreviated as E-threshold, and the dynamic water threshold as W-threshold. The comparison results between the current remaining resources (i.e., remaining electricity E and remaining water W) and the dynamic thresholds (i.e., E-threshold and W-threshold) are as follows: Case 1: E ≥ E threshold and W ≥ W threshold; This case indicates that there are sufficient remaining resources, so continue the cleaning task of the photovoltaic panels. Case 2: E ≥ E threshold and W < W threshold; This case indicates that the remaining water is insufficient, triggering a water shortage resupply command, requiring the drone to return to the resupply point; Case 3: E < E threshold and W ≥ W threshold; This case indicates that the remaining power is insufficient, triggering a power shortage resupply command, requiring the drone to return to the resupply point; Case 4: E < E threshold and W < W threshold; This case indicates that both the remaining water and the remaining power are insufficient, triggering a return-to-base command due to insufficient dual resources, requiring the drone to return to the resupply point.

[0068] This invention, in its embodiments, triggers different return-to-base resupply commands based on the type of resource deficiency (e.g., power shortage, water shortage, or both). This allows resupply points to anticipate the type of resource deficiency the drone is experiencing, enabling more efficient resource resupply upon the drone's return. For example, when a power shortage command is triggered, the drone's battery is replenished first; when a water shortage command is triggered, water is replenished first; and when both resources are insufficient, the slower-replenishing resource is prioritized based on the different replenishment rates of electricity and water. This configuration improves operational efficiency.

[0069] Based on the above embodiments, optionally, the cleaning progress of the drone can be obtained in real time, including: obtaining the coordinates of the starting cleaning point and the ending cleaning point on the photovoltaic panel, and obtaining the current coordinates of the drone in real time; and obtaining the cleaning progress based on the coordinates of the starting cleaning point, the ending cleaning point, and the current coordinates.

[0070] The coordinates can be, for example, latitude and longitude coordinates. For instance, the drone pre-loads a map showing the locations of the photovoltaic panels, containing the latitude and longitude coordinates of the two endpoints of each panel (e.g., the two shorter points to the left and right along the drone's operating direction). During cleaning, the drone first flies to the left endpoint, then begins its flight to the right endpoint to perform the cleaning task. Reaching the right endpoint signifies completion of the cleaning process. During flight, the drone can obtain its current position coordinates in real time via its positioning module. The cleaning progress is calculated by dividing the straight-line distance between the current position coordinates and the right endpoint (or the right endpoint itself) by the length of the photovoltaic panel (the straight-line distance between the left and right endpoints). This setup is simple to implement and provides accurate calculations of the cleaning progress.

[0071] Based on the above embodiments, optionally, there are multiple supply points, and the distance from the UAV to the nearest supply point is obtained in real time, including: calculating the straight-line distance between the UAV and each supply point based on the current coordinate position of the UAV and the coordinate position of each supply point obtained in real time; and selecting the minimum distance among the straight-line distances as the distance from the UAV to the nearest supply point.

[0072] Multiple resupply points are distributed at different locations along the edge of the photovoltaic array. The map pre-loaded on the drone also includes the latitude and longitude coordinates of all resupply points. During flight, the drone dynamically calculates the power threshold based on its current location, selecting the nearest resupply point in real time. This allows for more efficient use of power resources and avoids waste. It's understandable that the nearest resupply point changes dynamically during flight. For example, if there are multiple resupply points designated as the first, second, ..., Nth resupply point, when the drone is at position A, the nearest resupply point is the second; when it is at position B, the nearest resupply point is the Nth. Furthermore, when the drone needs to return to a resupply point, it can also return to the nearest resupply point, thus shortening the return distance and improving operational efficiency.

[0073] It should be noted that the operation of collecting information such as remaining battery power, remaining water volume, and current location in real time by the drone does not require high computing power and will not affect the performance of the control system.

[0074] In summary, the embodiments of the present invention can achieve at least the following beneficial effects: Firstly, the embodiments of the present invention use dynamic threshold linkage calculation for water and electricity resources, which is conducive to the full utilization of electricity and water, reduces the number of times drones travel to and from the resupply point, and improves resource utilization.

[0075] Secondly, in this embodiment of the invention, the return to the replenishment point after completing the cleaning of the entire photovoltaic panel helps to avoid interruptions in the middle of the photovoltaic panel, reduce missed cleaning and re-cleaning, improve work efficiency, and reduce rework time.

[0076] Thirdly, in this embodiment of the invention, a safety gap at the edge of the photovoltaic panel is used as a dedicated breakpoint for positioning. While the drone is flying to the safety gap at the edge of the photovoltaic panel, it continues to perform the cleaning task on the photovoltaic panel. As a supplement to the second aspect of the technical solution, this further ensures that the drone returns to the airport only after the previous photovoltaic panel has been cleaned, thus ensuring the integrity of the cleaning process.

[0077] Fourthly, this embodiment of the invention sets up multiple resupply points. During flight, the UAV dynamically calculates its power threshold by selecting the nearest resupply point based on its current location, enabling more efficient use of power resources and avoiding waste. Furthermore, when the UAV needs to return to a resupply point, it can do so, shortening the return distance and improving operational efficiency.

[0078] Fifthly, the embodiments of the present invention, through full archiving of breakpoint parameters and adaptation of subsequent washing parameters, automatically match the original cleaning mode after replenishment, ensuring uniform cleaning effect and good adaptability to subsequent washing.

[0079] Sixthly, the technical solution provided by the embodiments of the present invention can be adapted to different models of photovoltaic cleaning drones and photovoltaic power stations with different layouts, supports flexible setting of temporary resupply points, is highly practical, highly adaptable, has a wide range of scenarios, and is easy to promote.

[0080] This invention also provides a control device for a photovoltaic cleaning drone. This device can be implemented using software and / or hardware and can be configured within the drone. This device can execute the control method for the photovoltaic cleaning drone provided in any embodiment of this invention and has corresponding beneficial effects.

[0081] in, Figure 7 This is a schematic diagram of a control device for a photovoltaic cleaning drone provided in an embodiment of the present invention. See also... Figure 7 The device includes: The data acquisition module 210 is used to acquire in real time the drone's cleaning mode, minimum cleaning target, cleaning progress of executing the minimum cleaning target, flight power consumption coefficient, and distance to the nearest supply point; The dynamic water volume threshold calculation module 220 is used to obtain the water volume required to complete the minimum cleaning target based on the cleaning mode and cleaning progress, and use it as the dynamic water volume threshold. The dynamic power threshold calculation module 230 is used to obtain the power required to complete the minimum cleaning target based on the cleaning mode and cleaning progress, as the first power; determine the power required to return to the nearest supply point based on the flight power consumption coefficient and the distance to the nearest supply point, as the second power; and obtain the dynamic power threshold based on the first power and the second power. The return-to-home decision module 240 is used to determine whether the drone needs to return to the resupply point based on dynamic power thresholds and dynamic water thresholds.

[0082] Optionally, the dynamic water volume threshold calculation module 220 includes: The water consumption coefficient determination unit is used to obtain the water consumption coefficient based on the cleaning mode; The dynamic water volume threshold calculation unit is used to determine the minimum water volume required to achieve the cleaning target based on the water consumption coefficient and cleaning progress, and uses this as the dynamic water volume threshold.

[0083] Optionally, the dynamic power threshold calculation module 230 includes: The cleaning power consumption coefficient determination unit is used to obtain the cleaning power consumption coefficient according to the cleaning mode; The dynamic power threshold calculation unit is used to obtain the power required to complete the minimum cleaning target based on the cleaning power consumption coefficient and cleaning progress.

[0084] The dynamic power threshold calculation module 230 also includes: The flight power consumption coefficient determination unit is used to acquire the remaining water volume after the UAV completes the minimum cleaning target in real time; and to determine the flight power consumption coefficient based on the remaining water volume; wherein, the remaining water volume is positively correlated with the flight power consumption coefficient.

[0085] Optionally, the minimum cleaning objective is to clean the entire photovoltaic panel.

[0086] Optionally, the return-to-home determination module 240 includes: The minimum target completion unit is used to make judgments based on the cleaning progress. If the minimum cleaning target is started but not completed, the drone is controlled to continue to execute the minimum cleaning target until it is completed. The data recording unit is used to record the position of the lowest completed cleaning target as the breakpoint position; and to record the cleaning mode used by the lowest completed cleaning target as the cleaning mode before the interruption. The return-to-home control unit is used to control the drone's return to the resupply point.

[0087] Optionally, the return-to-home determination module 240 also includes: The pre-return position control unit is used to control the drone to fly to the safe gap between the edge of the currently cleaned photovoltaic panel and the edge of the next photovoltaic panel; the position of the safe gap is recorded as the breakpoint position.

[0088] The control device of the photovoltaic cleaning drone also includes: a breakpoint resume cleaning module, which is used to control the drone to locate the breakpoint position after the drone is refueled; and to control the drone to automatically match the cleaning mode before the interruption as the cleaning mode to execute the new minimum cleaning target.

[0089] Optionally, the data acquisition module 210 is also used to acquire the remaining battery power and remaining water volume of the drone in real time; The return-to-home judgment module 240 also includes a threshold judgment unit, which determines whether a resupply command is triggered if the remaining battery power is less than the dynamic battery power threshold or the remaining water volume is less than the dynamic water volume threshold, and the drone needs to return to the resupply point.

[0090] Optionally, the data acquisition module 210 is also used to acquire the coordinates of the starting cleaning point and the ending cleaning point on the photovoltaic panel, as well as the current coordinates of the drone in real time; and to obtain the cleaning progress based on the coordinates of the starting cleaning point, the ending cleaning point, and the current coordinates.

[0091] Optionally, there are multiple supply points; the data acquisition module 210 is also used to calculate the straight-line distance between the UAV and each supply point based on the real-time acquired current coordinate position of the UAV and the coordinate position of each supply point; and select the minimum distance among the straight-line distances as the distance for the UAV to reach the nearest supply point.

[0092] This invention also provides a drone, which includes: a drone main structure, a battery system, a cleaning system, and a control system. The control system executes the control method of the photovoltaic cleaning drone provided in any embodiment of this invention and has corresponding beneficial effects.

[0093] Optionally, the control system includes a resource acquisition module, which includes a power acquisition unit, a water acquisition unit, etc. For example, the resource acquisition module acquires data at a frequency of once per second to ensure real-time and accurate data.

[0094] Optionally, the control system includes a task and operating condition acquisition module, which comprises a visual recognition unit, a positioning unit, a current cleaning mode acquisition unit, and a flight distance calculation unit. The visual recognition unit identifies the current level of dirt on the photovoltaic panels and the remaining cleaning area. The positioning unit performs GPS and LiDAR fusion positioning to accurately obtain the UAV's current location and the photovoltaic panel array layout information. The current cleaning mode acquisition unit acquires the cleaning mode, such as high-pressure cleaning or low-pressure cleaning. The flight distance calculation unit calculates the distance from the current location to each resupply point.

[0095] Optionally, the control system includes a core control module, which is used to receive data collected by the resource acquisition module and the task and operating condition acquisition module, perform dynamic water volume threshold calculation and dynamic power threshold calculation, trigger return / resupply command, record breakpoints, and match recycle parameters, etc.

[0096] Optionally, the control system includes a communication module for communication between the UAV and the ground control terminal and temporary resupply points, transmitting resource data, operational status, breakpoint information, and receiving ground control commands.

[0097] Optionally, the cleaning system includes nozzles, water tanks, etc. The cleaning system receives instructions from the core control module, adjusts water pressure and flow rate, performs cleaning operations, and synchronously feeds back the cleaning status to the trusted control module.

[0098] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0099] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A control method for a photovoltaic cleaning drone, characterized in that, include: The system can acquire in real time the drone's cleaning mode, cleaning progress at the minimum cleaning target, flight power consumption coefficient, and distance to the nearest resupply point. Based on the cleaning mode and the cleaning progress, the amount of water required to complete the minimum cleaning target is obtained and used as a dynamic water volume threshold. Based on the cleaning mode and the cleaning progress, the amount of electricity required to complete the minimum cleaning target is obtained, which is used as the first amount of electricity. Based on the flight power consumption coefficient and the distance to the nearest resupply point, the amount of electricity required to return to the nearest resupply point is determined as the second amount of electricity; A dynamic power threshold is obtained based on the first power level and the second power level; Based on the dynamic power threshold and the dynamic water threshold, it is determined whether the drone needs to return to the resupply point.

2. The control method for a photovoltaic cleaning drone according to claim 1, characterized in that, The step of obtaining the water volume required to complete the minimum cleaning target based on the cleaning mode and the cleaning progress, and using it as a dynamic water volume threshold, includes: The water consumption coefficient is obtained based on the cleaning mode. Based on the water consumption coefficient and the cleaning progress, the amount of water required to complete the minimum cleaning target is obtained and used as a dynamic water volume threshold.

3. The control method for a photovoltaic cleaning drone according to claim 1, characterized in that, The step of obtaining the power required to complete the minimum cleaning target based on the cleaning mode and the cleaning progress includes: Based on the cleaning mode, the cleaning power consumption coefficient is obtained; Based on the cleaning power consumption coefficient and the cleaning progress, the amount of electricity required to complete the minimum cleaning target is obtained.

4. The control method for a photovoltaic cleaning drone according to claim 1, characterized in that, Before determining the amount of electricity required to return to the nearest resupply point based on the flight power consumption coefficient and the distance to the nearest resupply point, the method further includes: Real-time acquisition of the remaining water volume after the drone completes the minimum cleaning target; The flight power consumption coefficient is determined based on the remaining water volume; wherein the remaining water volume is positively correlated with the flight power consumption coefficient.

5. The control method for a photovoltaic cleaning drone according to any one of claims 1-4, characterized in that, The minimum cleaning objective is to clean the entire photovoltaic panel.

6. The control method for a photovoltaic cleaning drone according to claim 1, characterized in that, After determining that the drone needs to return to the resupply point based on the dynamic power threshold and the dynamic water threshold, the method further includes: Based on the cleaning progress, if the minimum cleaning target is started but not completed, the drone is controlled to continue executing the minimum cleaning target until it is completed. Record the position of the currently completed minimum cleaning target as the breakpoint position; record the cleaning mode used by the currently completed minimum cleaning target as the cleaning mode before interruption. Control the drone to return to the resupply point.

7. The control method for a photovoltaic cleaning drone according to claim 6, characterized in that, The recording of the current position of the lowest cleaning target, as the breakpoint position, includes: Control the drone to fly to a safe gap between the edge of the currently cleaned photovoltaic panel and the edge of the next photovoltaic panel; The location of the safety gap is recorded as the breakpoint location.

8. The control method for a photovoltaic cleaning drone according to claim 6, characterized in that, After controlling the drone to return to the resupply point, the method further includes: After resupplying the drone, control the drone to locate the breakpoint. The drone is controlled to automatically match the pre-interruption cleaning mode as the new minimum cleaning target cleaning mode.

9. The control method for a photovoltaic cleaning drone according to claim 1, characterized in that, The step of determining whether the drone needs to return to the resupply point based on the dynamic power threshold and the dynamic water threshold includes: The remaining battery power and water volume of the drone can be obtained in real time. If the remaining battery power is less than the dynamic battery power threshold, or the remaining water volume is less than the dynamic water volume threshold, a resupply command is triggered, and the drone needs to return to the resupply point.

10. The control method for a photovoltaic cleaning drone according to claim 1, characterized in that, Real-time acquisition of the cleaning progress of the drone, including: The coordinates of the starting cleaning point and the ending cleaning point on the photovoltaic panel are obtained, as well as the current coordinates of the drone in real time. The cleaning progress is obtained based on the coordinates of the starting cleaning point, the ending cleaning point, and the current coordinates.

11. The control method for a photovoltaic cleaning drone according to claim 1, characterized in that, There are multiple supply points; the distance from the drone to the nearest supply point is obtained in real time, including: Based on the real-time acquired current coordinates of the UAV and the coordinates of each supply point, the straight-line distance between the UAV and each supply point is calculated. The minimum distance among all straight-line distances is selected as the distance for the UAV to reach the nearest supply point.

12. A control device for a photovoltaic cleaning drone, characterized in that, include: The data acquisition module is used to acquire in real time the cleaning mode of the UAV, the cleaning progress of the minimum cleaning target, the flight power consumption coefficient, and the distance to the nearest supply point; The dynamic water volume threshold calculation module is used to obtain the water volume required to complete the minimum cleaning target based on the cleaning mode and the cleaning progress, and use it as the dynamic water volume threshold. The dynamic power threshold calculation module is used to obtain the power required to complete the minimum cleaning target based on the cleaning mode and the cleaning progress, and use it as the first power. Based on the flight power consumption coefficient and the distance to the nearest resupply point, the amount of electricity required to return to the nearest resupply point is determined as the second amount of electricity; a dynamic power threshold is obtained based on the first amount of electricity and the second amount of electricity. The return-to-home determination module is used to determine whether the drone needs to return to the resupply point based on the dynamic power threshold and the dynamic water threshold.

13. A drone, characterized in that, include: The drone includes a main structure, a battery system, a cleaning system, and a control system, wherein the control system executes the control method for the photovoltaic cleaning drone as described in any one of claims 1-11.

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