CN117163305A - Method and device for detecting power system of unmanned aerial vehicle - Google Patents

Abstract

The application provides a method and a device for detecting an unmanned aerial vehicle power system, which can effectively detect the state of the unmanned aerial vehicle power system. The method comprises the following steps: acquiring flight information of an unmanned aerial vehicle, wherein the flight information comprises environmental information of an environment where the unmanned aerial vehicle is located and/or flight state information of the unmanned aerial vehicle; according to the flight information, determining the efficiency of a power system of the unmanned aerial vehicle; and determining whether the power system is abnormal according to the efficiency of the power system.

Description

Method and device for detecting UAV power system

Technical field

Embodiments of the present application relate to the field of UAVs, and more specifically, to a method and device for detecting a UAV power system.

Background technique

The power system of a drone is easily affected by the environment and the state of the power system, which can lead to a decrease in the controllability of the drone and even flight safety and other issues. For this reason, how to effectively detect the status of the UAV power system has become an urgent problem to be solved.

Contents of the invention

Embodiments of the present application provide a method and device for detecting a UAV power system, which can effectively detect the status of the UAV power system.

In a first aspect, a method for detecting a power system of a UAV is provided. The method includes: obtaining flight information of the UAV, where the flight information includes environmental information of the environment in which the UAV is located and/or the Flight status information of the drone; determine the efficiency of the power system of the drone based on the flight information; determine whether an abnormality occurs in the power system based on the efficiency of the power system.

In the embodiment of the present application, the efficiency of the power system of the UAV can be determined based on the environmental information and/or flight status information of the UAV. Since the efficiency of the power system may change when an abnormality occurs in the power system, therefore, according to The efficiency of the power system can effectively detect whether an abnormality occurs in the power system, so that troubleshooting can be carried out in a timely manner after an abnormality occurs in the power system to ensure the safety of the drone.

In a possible implementation, the environmental information includes at least one of the following: atmospheric pressure, atmospheric temperature, and atmospheric density where the drone is located.

In a possible implementation, the flight status information includes at least one of the following: a PWM signal of a power shaft of the power system, a voltage of the energy system of the drone, and a current of the energy system. , information on the flight speed, flight attitude and flight angle of the UAV.

In a possible implementation, determining the efficiency of the power system of the UAV according to the flight information includes: calculating the efficiency of the power system based on the EKF algorithm according to the flight information. By using the extended Kalman filter to fuse and update the flight information of the UAV, the efficiency of the UAV's power system can be accurately calculated and evaluated.

In a possible implementation, calculating the efficiency of the power system based on the flight information and the EKF algorithm includes: obtaining the flight status information based on the flight status information and the EKF algorithm. The corresponding optimal estimated value; performing information fusion on the environmental information and the optimal estimated value to obtain the efficiency of the power system.

Since the sensors in the UAV are noisy, it is impossible to directly fuse the environmental information and the flight status information to calculate the efficiency of the power system. Therefore, in this embodiment, the flight status information is processed by EKF to obtain the corresponding The efficiency of the power system can be accurately obtained by fusing the optimal estimate with environmental information.

In a possible implementation, the efficiency of the power system is the ratio of the theoretical power consumption of the UAV in the current state to the actual power consumption, and the power is determined based on the efficiency of the power system. Whether an abnormality occurs in the system includes: if the ratio of the theoretical power consumption to the actual power consumption is less than a threshold, determining that an abnormality occurs in the power system.

In a possible implementation, the efficiency of the power system is the actual power consumption of the UAV in the current state, and determining whether an abnormality occurs in the power system according to the efficiency of the power system includes: : If the difference between the actual power consumption and the theoretical power consumption of the drone in the current state is greater than the threshold, it is determined that an abnormality occurs in the power system.

When an abnormality occurs in the power system, the power consumption of the power system may change, resulting in a difference from the theoretically estimated power consumption of the power system. Based on this, it can be determined whether an abnormality occurs in the power system.

In a possible implementation, the method further includes: sending information on the efficiency of the power system and/or a result of whether an abnormality occurs in the power system to the remote controller and server of the drone.

In a second aspect, a device for detecting the power system of an unmanned aerial vehicle is provided. The device includes: a collection module for acquiring flight information of the unmanned aerial vehicle. The flight information includes environmental information of the environment in which the unmanned aerial vehicle is located. and/or the flight status information of the drone; a processing module configured to determine the efficiency of the power system of the drone based on the flight information; the processing module is also configured to determine the efficiency of the power system based on the flight information. Efficiency, determine whether an abnormality occurs in the power system.

In a possible implementation, the environmental information includes at least one of the following: atmospheric pressure, atmospheric temperature, and atmospheric density where the drone is located.

In a possible implementation, the flight status information includes at least one of the following: a PWM signal of a power shaft of the power system, a voltage of the energy system of the drone, and a current of the energy system. , information on the flight speed, flight attitude and flight angle of the UAV.

In a possible implementation, the processing module is specifically configured to: calculate the efficiency of the power system based on the EKF algorithm according to the flight information.

In a possible implementation, the processing module is specifically configured to: obtain the optimal estimated value corresponding to the flight status information based on the EKF algorithm; and compare the environmental information and the The optimal estimated value is used for information fusion to obtain the efficiency of the power system.

In a possible implementation, the efficiency of the power system is the ratio of the theoretical power consumption of the drone in the current state to the actual power consumption, and the processing module is specifically configured to: if the theoretical power consumption If the ratio to the actual power consumption is less than the threshold, it is determined that an abnormality occurs in the power system.

In a possible implementation, the efficiency of the power system is the actual power consumption of the UAV in the current state, and the processing module is specifically configured to: if the actual power consumption of the UAV in the current state If the difference between the power consumption and the theoretical power consumption is greater than the threshold, it is determined that an abnormality occurs in the power system.

In a possible implementation, the device further includes a sending module for sending information about the efficiency of the power system and/or whether an abnormality occurs in the power system to the remote controller and server of the drone. the result of.

In a third aspect, a device for detecting a drone power system is provided, including a processor configured to execute computer instructions stored in a memory, so that the device implements the first aspect or any possibility of the first aspect. The method described in the implementation.

A fourth aspect provides a computer-readable storage medium for storing a computer program. When the computer program is executed by a computing device, the computing device implements the first aspect or any possible method of the first aspect. The method described in Implementation.

Description of drawings

In order to explain the technical solutions of the embodiments of the present application more clearly, the drawings required to be used in the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. Those of ordinary skill in the art can also obtain other drawings based on the drawings without exerting creative efforts.

Figure 1 is a schematic flow chart of a method for detecting a drone power system according to an embodiment of the present application.

FIG. 2 is a schematic diagram of a possible specific implementation of the method shown in FIG. 1 .

Figure 3 is a schematic flow chart of a device for detecting a drone power system according to an embodiment of the present application.

Figure 4 is a schematic flowchart of a device for detecting a drone power system according to an embodiment of the present application.

Detailed ways

The technical solutions in this application will be described below with reference to the accompanying drawings.

The power system of the drone includes a motor, an electronic speed regulator, a propeller, and an energy system such as a battery. The electronic speed regulator is used to control the speed of the motor based on the throttle signal sent by the flight controller (referred to as the flight controller), so that the motor drives the drone. The propeller turns. The efficiency of the power system is related to the parameters of the propeller, motor, and electronic speed regulator, as well as to the combination of the propeller, motor, and electronic speed regulator. In addition, when the power system of the drone is fixed, the power system is easily affected by the environment in which it is located, such as atmospheric pressure, atmospheric density, atmospheric temperature, etc. It is also easily affected by the status of the power system, such as whether the blades are damaged, whether the motor is blocked, Whether the ESC is faulty or not, etc. When the UAV is flying normally, the efficiency of the power system is high. If the UAV flies when its power system is abnormal, the aerodynamic efficiency of the propeller will be significantly reduced compared to normal flight. In order to provide sufficient lift, the propeller needs to increase its speed, which will cause problems such as a decrease in the efficiency of the power system, a decrease in the controllability of the drone, and even affect the flight safety of the drone.

To this end, this application provides a solution for detecting the power system of a drone, aiming to determine whether there is a problem with the power system of the drone by testing the efficiency of the power system of the drone.

Figure 1 shows a method for detecting a UAV power system according to an embodiment of the present application. This method is applied to aircraft, especially unmanned aerial vehicles, i.e. drones. The UAV in the embodiment of the present application may be, for example, a six-arm UAV, which includes six propellers. As shown in Figure 1, method 100 includes some or all of the following steps.

In step 110, the flight information of the drone is obtained.

The flight information includes environmental information of the environment in which the drone is located and/or flight status information of the drone.

In step 120, the efficiency of the UAV's power system is determined based on the flight information.

In step 130, it is determined whether an abnormality occurs in the power system based on the efficiency of the power system.

The environmental information may be parameters of the atmospheric environment in which the drone is located, including, for example, at least one of the following: atmospheric pressure, atmospheric temperature, atmospheric density, etc. where the drone is located.

The flight status information is used to characterize the working status of each system in the drone and/or the physical state in which the drone is currently flying. For example, it includes at least one of the following: pulse width modulation of the power axis of the power system ( pulsewidth modulation (PWM) signal, the voltage of the UAV's energy system, the current of the energy system, the UAV's flight speed, flight attitude and flight angle and other information. The flight speed information includes linear speed and angular speed.

The power shaft in the power system of the drone may be, for example, a propeller, etc., and the PWM signal of the power shaft may be, for example, a throttle signal sent to it by the flight control. The energy system of the drone may be, for example, a device for providing electrical energy such as a battery of the drone.

In the embodiment of the present application, the efficiency of the power system of the UAV can be determined based on the environmental information and/or flight status information of the UAV, for example, the environmental information and the flight status information can be fused. Since the efficiency of the power system may change when an abnormality occurs in the power system, based on the efficiency of the power system, it can be effectively detected whether an abnormality occurs in the power system, so that troubleshooting can be carried out in a timely manner after an abnormality occurs in the power system to ensure that Drone safety.

In some embodiments, in step 120, the efficiency of the power system can be calculated based on the extended Kalman filter (EKF) algorithm according to the flight information of the drone. Among them, the efficiency of the power system can also be referred to as power efficiency.

The extended Kalman filter algorithm is an extended form of the standard Kalman filter algorithm in nonlinear situations. By using the extended Kalman filter to fuse and update the flight information of the UAV, the efficiency of the UAV's power system can be accurately calculated and evaluated.

For example, based on the flight status information and the EKF algorithm, the optimal estimate corresponding to the flight status information can be obtained; and the optimal estimate of the environmental information and flight status information can be fused to obtain the efficiency of the power system.

Due to the high noise of sensors in UAVs, it is impossible to directly fuse environmental information and flight status information to calculate the efficiency of the power system. After EKF processing of the flight status information, the corresponding optimal estimated value can be obtained. By fusing the optimal estimated value of the flight status information with the environmental information, the efficiency of the power system can be accurately obtained.

When an abnormality occurs in the power system, the power consumption of the power system may change, resulting in a difference from the theoretically estimated power consumption of the power system. Based on this, it can be determined whether an abnormality occurs in the power system.

Specifically, when the UAV is flying normally, the power consumption of the power system can be equal to the theoretically estimated power consumption of the power system, or there may be a deviation from the theoretically estimated power consumption of the power system. Within the acceptable range. In the event of an abnormality in the power system, the power consumption of the power system will be higher to meet the current normal flight needs. At this time, part of the total power consumption of the power system is used to maintain the original effective power consumption of normal flight, while the other part is used to overcome the additional power consumption caused by abnormal power system. Therefore, the efficiency of a powertrain can be reflected by its power consumption.

For example, the ratio between the theoretical power consumption and the actual power consumption of the drone in the current state can be used to characterize the efficiency of the power system. At this time, in step 130, if the ratio between the theoretical power consumption and the actual power consumption of the drone in the current state is less than the threshold K1, it is determined that an abnormality occurs in the power system.

For another example, the actual power consumption of the drone in its current state can be used to characterize the efficiency of the power system. At this time, in step 130, if the difference between the actual power consumption and the theoretical power consumption of the drone in the current state is greater than the threshold K2, it is determined that an abnormality occurs in the power system.

K1 and K2 may be, for example, power consumption values calculated based on theory. K1 can be equal to 1, that is, as long as the ratio between theoretical power consumption and actual power consumption is not equal to 1, the power system is considered abnormal. However, in practical applications, K1 is usually set to less than 1, that is, the ratio between the theoretical power consumption and the actual power consumption of the power system is less than the tolerable level K1, and then the power system is considered abnormal.

As an example, assume K1 = 0.8, the theoretical power consumption of the power system is 6KW, the current actual power consumption of the power system is 10KW, the ratio between the theoretical power consumption and the actual power consumption is 0.6, since 0.6 is less than 0.8, it can be considered that the power consumption An exception occurred in the system.

Similarly, K2 can wait for 0, that is, as long as the actual power consumption is not equal to the theoretical power consumption, the power system is considered to be faulty. However, in practical applications, K2 is usually set to be greater than 0, that is, when the difference between the theoretical power consumption and the actual power consumption of the power system exceeds the tolerable level K2, the power system is considered abnormal.

As an example, assuming K2 = 2KW, the theoretical power consumption of the power system is 6KW, and the current actual power consumption of the power system is 10KW, then the difference between the theoretical power consumption and its actual power consumption is 4KW. Since 4KW is greater than 2KW, then it can It is believed that there is an abnormality in the power system.

In addition to its environmental information and flight status information, the power consumption of the power system is also related to the weight of the drone. For example, as shown in Table 1, the relationship between the load of the drone and the power consumption of the power system. When the load of the drone is X1, the power consumption of the power system is W1; when the load of the drone is X2, the power consumption of the power system is W2; ...; when the load of the drone is Among them, the load X1<X2<...<Xn, the corresponding power consumption W1<W2<...<Wn. In other words, the greater the load of the drone, the greater the power consumption of the power system.

Table I

It can be understood that when an abnormality occurs in the power system, such as damaged blades, motor blockage, ESC failure, etc., the efficiency of the power system is reduced. However, there is a situation where the current efficiency of the power system calculated based on the current flight information of the power system is improved compared to the theoretical efficiency. At this time, it can also be judged that other problems have occurred in the work of the UAV. For example, there may be no The load on the human machine is reduced, resulting in a higher efficiency of the power system. At this time, you can check whether the drone does not carry a load of sufficient weight, or whether the load drops during flight.

As an example, as shown in Figure 2, the power system of the UAV is detected to obtain the environmental information of the environment where the UAV is located, that is, atmospheric parameters such as temperature, pressure and density; control signals such as PWM signals, energy systems Information such as voltage and current; flight status information such as flight speed and flight attitude. Based on the EKF algorithm, flight status information such as linear velocity, angular velocity, attitude parameters, etc. are processed to obtain the corresponding optimal estimated values of linear velocity, angular velocity, attitude parameters, etc. By performing information fusion calculations on the obtained best estimate and environmental information, the actual power consumption P1 of the UAV during flight can be obtained.

Through a large amount of actual flight data under normal conditions and based on aerodynamic theory, the optimally estimated theoretical power consumption P2 can be obtained. Optionally, a power system efficiency benchmark table can be set, so that the theoretical efficiency of the power system can be obtained by querying the power system efficiency benchmark table. The power system efficiency benchmark table can, for example, include corresponding theories under different environmental information and flight status information. efficiency value.

Finally, the actual efficiency of the power system is determined based on P1 and P2, and whether an abnormality occurs in the power system is determined based on whether the difference between the actual efficiency and the theoretical efficiency exceeds the threshold.

In some embodiments, the method 100 further includes: sending information on the efficiency of the power system and/or a result of whether an abnormality occurs in the power system to the remote controller and server of the drone. This allows the remote controller and the server to perform corresponding operations based on information about the efficiency of the power system and/or whether abnormal results occur in the power system to reduce the probability of risks to the drone.

This application also provides a device for detecting the power system of a drone. As shown in Figure 3, the device 200 includes a collection module 210 and a processing module 220.

Among them, the collection module 210 is used to obtain the flight information of the drone. The flight information includes environmental information of the environment where the drone is located and/or flight status information of the drone. The processing module 220 is used to determine the efficiency of the power system of the UAV based on the flight information, and determine whether an abnormality occurs in the power system based on the efficiency of the power system.

In some embodiments, the environmental information includes at least one of the following: atmospheric pressure, atmospheric temperature, and atmospheric density where the drone is located.

In some embodiments, the flight status information includes at least one of the following: PWM signal of the power axis of the power system, voltage of the energy system of the drone, current of the energy system, flight speed and flight attitude of the drone. information.

In some embodiments, the processing module 220 is specifically configured to calculate the efficiency of the power system based on the flight information and the EKF algorithm.

In a possible implementation, the efficiency of the power system is the ratio of the theoretical power consumption to the actual power consumption of the UAV in the current state. The processing module 220 is specifically used to: if the ratio of the theoretical power consumption to the actual power consumption is less than Threshold to determine an abnormality in the power system.

In a possible implementation, the efficiency of the power system is the actual power consumption of the UAV in the current state, and the processing module 220 is specifically used to: If the actual power consumption of the UAV in the current state is equal to the theoretical power consumption If the difference between them is greater than the threshold, it is determined that an abnormality occurs in the power system.

In some embodiments, the device 200 also includes a sending module 230, which is used to send information about the efficiency of the power system and/or the result of whether an abnormality occurs in the power system to the remote controller and server of the drone.

It should be understood that for specific details of the device 200 for detecting the power system of an unmanned aerial vehicle, reference can be made to the foregoing description of the method 100 for detecting the power system of an unmanned aerial vehicle. For the sake of brevity, details will not be described again here.

This application also provides a device for detecting the power system of a drone. As shown in Figure 4, the device 300 includes a processor 310. The processor 310 is used to execute computer instructions stored in the memory to enable the device 300 to implement any of the above implementations. Method 100 for detecting UAV power system described in the example. Optionally, the device 300 further includes a memory 320 for storing a computer program including instructions. The processor 310 and the memory 320 may be connected through a bus.

The device 300 may be, for example, a chip installed on a drone. The chip includes a processor and an interface circuit. The interface circuit is used to provide program instructions or data to the processor, and the processor is used to execute the program instructions to implement any of the above embodiments. The method 100 for detecting a drone power system. The implementation principles and technical effects are similar to the above-mentioned method 100. For details, please refer to the foregoing description of the method 100. For the sake of simplicity, they will not be described again here.

The present application also provides a computer-readable storage medium, including computer instructions. When the computer instructions are run on the device 300, the device 300 causes the device 300 to execute the method 100 for detecting a drone power system described in any of the above embodiments. The implementation principles and technical effects are similar to the above-mentioned method 100. For details, please refer to the foregoing description of the method 100. For the sake of simplicity, they will not be described again here.

The application also provides a computer program product, including computer readable code, or a non-volatile computer readable storage medium carrying the computer readable code. When the computer readable code is run in the device 300, the device 300 The processor 310 in 300 executes the method 100 for detecting the UAV power system described in any of the above embodiments. The implementation principles and technical effects are similar to the above-mentioned method 100. For details, please refer to the foregoing description of the method 100. For the sake of simplicity, they will not be described again here.

It should be noted that, on the premise of no conflict, the various embodiments described in this application and/or the technical features in each embodiment can be combined with each other arbitrarily, and the technical solution obtained after the combination should also fall within the protection scope of this application. . Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each specific application, but such implementations should not be considered beyond the scope of this application.

Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be described again here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit.

If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program code. .

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person familiar with the technical field can easily think of various equivalent methods within the technical scope disclosed in the present application. Modification or replacement, these modifications or replacements shall be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims (18)

1. A method for detecting the power system of an unmanned aerial vehicle, characterized in that the method includes: Obtain flight information of the UAV, the flight information including environmental information of the environment in which the UAV is located and/or flight status information of the UAV; Determine the efficiency of the power system of the UAV based on the flight information; Based on the efficiency of the power system, it is determined whether an abnormality occurs in the power system. 2. The method according to claim 1, characterized in that the environmental information includes at least one of the following: The atmospheric pressure, atmospheric temperature and atmospheric density where the drone is located. 3. The method according to claim 1, characterized in that the flight status information includes at least one of the following: The pulse width modulation PWM signal of the power axis of the power system, the voltage of the energy system of the UAV, the current of the energy system, the flight speed, flight attitude and flight angle information of the UAV. 4. The method according to any one of claims 1 to 3, wherein determining the efficiency of the power system of the UAV according to the flight information includes: According to the flight information and based on the extended Kalman filter EKF algorithm, the efficiency of the power system is calculated. 5. The method of claim 4, wherein calculating the efficiency of the power system based on the flight information and the EKF algorithm includes: According to the flight status information, based on the EKF algorithm, obtain the optimal estimate corresponding to the flight status information; Information fusion is performed on the environmental information and the optimal estimated value to obtain the efficiency of the power system. 6. The method according to any one of claims 1 to 3, characterized in that the efficiency of the power system is the ratio of the theoretical power consumption of the drone in the current state to the actual power consumption, Determining whether an abnormality occurs in the power system according to the efficiency of the power system includes: If the ratio of the theoretical power consumption to the actual power consumption is less than a threshold, it is determined that an abnormality occurs in the power system. 7. The method according to any one of claims 1 to 3, characterized in that the efficiency of the power system is the actual power consumption of the drone in the current state, Determining whether an abnormality occurs in the power system according to the efficiency of the power system includes: If the difference between the actual power consumption and the theoretical power consumption of the UAV in the current state is greater than the threshold, it is determined that an abnormality occurs in the power system. 8. The method according to any one of claims 1 to 3, characterized in that the method further comprises: Send information on the efficiency of the power system and/or a result of whether an abnormality occurs in the power system to the remote controller and server of the drone. 9. A device for detecting the power system of a drone, characterized in that the device includes: An acquisition module, used to obtain flight information of the UAV, where the flight information includes environmental information of the environment in which the UAV is located and/or flight status information of the UAV; A processing module configured to determine the efficiency of the power system of the UAV based on the flight information; The processing module is also used to determine whether an abnormality occurs in the power system according to the efficiency of the power system. 10. The device according to claim 9, characterized in that the environmental information includes at least one of the following: The atmospheric pressure, atmospheric temperature and atmospheric density where the drone is located. 11. The device according to claim 9, wherein the flight status information includes at least one of the following: The pulse width modulation PWM signal of the power axis of the power system, the voltage of the energy system of the UAV, the current of the energy system, the flight speed, flight attitude and flight angle information of the UAV. 12. The device according to any one of claims 9 to 11, characterized in that the processing module is specifically used for: According to the flight information and based on the extended Kalman filter EKF algorithm, the efficiency of the power system is calculated. 13. The device according to claim 12, characterized in that the processing module is specifically used to: According to the flight status information, based on the EKF algorithm, obtain the optimal estimate corresponding to the flight status information; Information fusion is performed on the environmental information and the optimal estimated value to obtain the efficiency of the power system. 14. The device according to any one of claims 9 to 11, wherein the efficiency of the power system is the ratio of the theoretical power consumption of the drone in the current state to the actual power consumption, and the The processing module is specifically used for: If the ratio of the theoretical power consumption to the actual power consumption is less than a threshold, it is determined that an abnormality occurs in the power system. 15. The device according to any one of claims 9 to 11, characterized in that the efficiency of the power system is the actual power consumption of the drone in the current state, The processing module is specifically used for: If the difference between the actual power consumption and the theoretical power consumption of the UAV in the current state is greater than the threshold, it is determined that an abnormality occurs in the power system. 16. The device according to any one of claims 9 to 11, characterized in that the device further comprises: A sending module, configured to send information on the efficiency of the power system and/or a result of whether an abnormality occurs in the power system to the remote controller and server of the drone. 17. A device for detecting the power system of an unmanned aerial vehicle, characterized by comprising a processor, the processor being configured to execute computer instructions stored in a memory, so that the device implements the method according to any one of claims 1 to 8 the method described. 18. A computer-readable storage medium, characterized in that it is used to store a computer program, and when the computer program is executed by a computing device, the computing device implements the method according to any one of claims 1 to 8. method described.