CN117163305A - Method and device for detecting power system of unmanned aerial vehicle - Google Patents
Method and device for detecting power system of unmanned aerial vehicle Download PDFInfo
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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
Technical Field
The embodiment of the application relates to the field of unmanned aerial vehicles, and in particular relates to a method and a device for detecting a power system of an unmanned aerial vehicle.
Background
The power system of the unmanned aerial vehicle is easily influenced by the environment where the unmanned aerial vehicle is located and the state of the power system, so that the controllability of the unmanned aerial vehicle is reduced, and even the problems of flight safety and the like occur. Therefore, how to effectively detect the state of the power system of the unmanned aerial vehicle is a problem to be solved.
Disclosure of Invention
The embodiment of 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.
In a first aspect, a method of detecting an unmanned power system is provided, the method comprising: 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.
According to the embodiment of the application, the efficiency of the power system of the unmanned aerial vehicle can be determined according to the environmental information and/or the flight state information of the unmanned aerial vehicle, and the efficiency of the power system can be changed under the condition that the power system is abnormal, so that whether the power system is abnormal or not can be effectively detected according to the efficiency of the power system, and therefore, fault investigation can be timely carried out after the power system is abnormal, and the safety of the unmanned aerial vehicle is ensured.
In one possible implementation, the environmental information includes at least one of: the unmanned aerial vehicle is located atmospheric pressure, atmospheric temperature and atmospheric density.
In one possible implementation, the flight status information includes at least one of: PWM signals of a power shaft of the power system, voltage of an energy system of the unmanned aerial vehicle, current of the energy system, and information of flight speed, flight attitude and flight angle of the unmanned aerial vehicle.
In one possible implementation manner, the determining the efficiency of the power system of the unmanned aerial vehicle according to the flight information includes: and calculating the efficiency of the power system based on an EKF algorithm according to the flight information. By using the extended Kalman filter to fuse and update the flight information of the unmanned aerial vehicle, the efficiency of the power system of the unmanned aerial vehicle can be accurately calculated and estimated.
In one possible implementation, the calculating the efficiency of the power system based on an EKF algorithm according to the flight information includes: obtaining an optimal estimated value corresponding to the flight state information based on the EKF algorithm according to the flight state information; and carrying out information fusion on the environment information and the optimal estimated value to obtain the efficiency of the power system.
Because the noise of the sensor in the unmanned aerial vehicle is large, the information fusion of the environment information and the flight state information cannot be directly carried out to calculate the efficiency of the power system, in the embodiment, the flight state information is processed by the EKF to obtain the corresponding optimal estimated value, and the optimal estimated value and the environment information are fused to accurately obtain the efficiency of the power system.
In one possible implementation manner, the efficiency of the power system is a ratio of theoretical power consumption to actual power consumption of the unmanned aerial vehicle in a current state, and the determining whether the power system is abnormal according to the efficiency of the power system includes: and if the ratio of the theoretical power consumption to the actual power consumption is smaller than a threshold value, determining that the power system is abnormal.
In one possible implementation manner, the efficiency of the power system is the actual power consumption of the unmanned aerial vehicle in the current state, and the determining whether the power system is abnormal according to the efficiency of the power system includes: and if the difference value between the actual power consumption and the theoretical power consumption of the unmanned aerial vehicle in the current state is larger than a threshold value, determining that the power system is abnormal.
Under the condition that the power system is abnormal, the power consumption of the power system may change, so that a difference exists between the power consumption of the power system and the power consumption of the power system estimated in theory, and whether the power system is abnormal or not can be judged based on the difference.
In one possible implementation, the method further includes: and sending information of the efficiency of the power system and/or a result of whether the power system is abnormal or not to a remote controller and a server of the unmanned aerial vehicle.
In a second aspect, there is provided an apparatus for detecting an unmanned aerial vehicle power system, the apparatus comprising: the unmanned aerial vehicle flight information acquisition module is used for 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; the processing module is used for determining the efficiency of the power system of the unmanned aerial vehicle according to the flight information; the processing module is also used for determining whether the power system is abnormal according to the efficiency of the power system.
In one possible implementation, the environmental information includes at least one of: the unmanned aerial vehicle is located atmospheric pressure, atmospheric temperature and atmospheric density.
In one possible implementation, the flight status information includes at least one of: PWM signals of a power shaft of the power system, voltage of an energy system of the unmanned aerial vehicle, current of the energy system, and information of flight speed, flight attitude and flight angle of the unmanned aerial vehicle.
In one possible implementation manner, the processing module is specifically configured to: and calculating the efficiency of the power system based on an EKF algorithm according to the flight information.
In one possible implementation manner, the processing module is specifically configured to: obtaining an optimal estimated value corresponding to the flight state information based on the EKF algorithm according to the flight state information; and carrying out information fusion on the environment information and the optimal estimated value to obtain the efficiency of the power system.
In one possible implementation manner, the efficiency of the power system is a ratio of theoretical power consumption to actual power consumption of the unmanned aerial vehicle in a current state, and the processing module is specifically configured to: and if the ratio of the theoretical power consumption to the actual power consumption is smaller than a threshold value, determining that the power system is abnormal.
In one possible implementation manner, the efficiency of the power system is the actual power consumption of the unmanned aerial vehicle in the current state, and the processing module is specifically configured to: and if the difference value between the actual power consumption and the theoretical power consumption of the unmanned aerial vehicle in the current state is larger than a threshold value, determining that the power system is abnormal.
In a possible implementation manner, the device further comprises a sending module, configured to send information of the efficiency of the power system and/or a result of whether the power system is abnormal to a remote controller and a server of the unmanned aerial vehicle.
In a third aspect, there is provided an apparatus for detecting an unmanned power system, comprising a processor for executing computer instructions stored in a memory to cause the apparatus to implement the method of the first aspect or any one of the possible implementations of the first aspect.
In a fourth aspect, a computer readable storage medium is provided for storing a computer program which, when executed by a computing device, causes the computing device to implement the method as described in the first aspect or any one of the possible implementations of the first aspect.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method of detecting an unmanned power system according to an embodiment of the application.
Fig. 2 is a schematic diagram of one possible implementation of the method shown in fig. 1.
Fig. 3 is a schematic flow chart of an apparatus for detecting a power system of an unmanned aerial vehicle according to an embodiment of the present application.
Fig. 4 is a schematic flow chart of an apparatus for detecting a power system of an unmanned aerial vehicle according to an embodiment of the present application.
Detailed Description
The technical scheme of the application will be described below with reference to the accompanying drawings.
The power system of the unmanned aerial vehicle comprises a motor, an electronic speed regulator, a propeller and an energy system such as a battery and the like, wherein the electronic speed regulator is used for controlling the rotating speed of the motor according to an accelerator signal sent by a flight controller (for short flight control), so that the motor drives the propeller to rotate. The efficiency of the power system is related to the respective parameters of the propeller, the motor and the electronic governor and also to the combination of the propeller, the motor and the electronic governor. In addition, when the power system of the unmanned aerial vehicle is fixed, the power system is easily affected by the environment where the power system is located, such as the atmospheric pressure, the atmospheric density, the atmospheric temperature and the like, and is also easily affected by the state of the power system, such as the state of whether a blade is broken, whether a motor is blocked, whether an electric regulator is faulty or not and the like. Under the condition that unmanned aerial vehicle normally flies, the efficiency of driving system is higher, if unmanned aerial vehicle flies under the circumstances that its driving system takes place unusual, then for the circumstances of normal flight, the screw aerodynamic efficiency obviously drops, in order to provide sufficient lift, the screw needs to increase the rotational speed to the efficiency that causes driving system drops, unmanned aerial vehicle's controllability decline scheduling problem even influences unmanned aerial vehicle's flight safety.
Therefore, the application provides a scheme for detecting the power system of the unmanned aerial vehicle, and aims to judge whether the power system of the unmanned aerial vehicle has a problem or not by detecting the efficiency of the power system of the unmanned aerial vehicle.
Fig. 1 illustrates a method of detecting an unmanned power system according to an embodiment of the present application. The method is applied to aircrafts, in particular unmanned aircrafts, namely unmanned aircrafts. The unmanned aerial vehicle of the embodiment of the application can be, for example, a six-radial-arm unmanned aerial vehicle, and comprises six propellers. As shown in fig. 1, method 100 includes some or all of the following steps.
In step 110, flight information of the drone is acquired.
The flight information comprises environment information of the environment where the unmanned aerial vehicle is located and/or flight state information of the unmanned aerial vehicle.
In step 120, the efficiency of the power system of the unmanned aerial vehicle is determined from the flight information.
In step 130, it is determined whether an abnormality in the power system has occurred based on the efficiency of the power system.
The environmental information may be a parameter of an atmospheric environment in which the unmanned aerial vehicle is located, for example, including at least one of: atmospheric pressure, atmospheric temperature, atmospheric density, etc. where the unmanned aerial vehicle is located.
The flight state information is used for representing the working state of each system in the unmanned aerial vehicle and/or the physical state of the unmanned aerial vehicle when the unmanned aerial vehicle is currently in flight, and comprises at least one of the following: pulse width modulation (pulse width modulation, PWM) signals of a power shaft of the power system, voltage of an energy system of the unmanned aerial vehicle, current of the energy system, flight speed, flight attitude, flight angle and the like of the unmanned aerial vehicle. The information of the flying speed includes a linear speed, an angular speed, and the like.
The power shaft in the power system of the unmanned aerial vehicle may be, for example, a propeller or the like, and the PWM signal of the power shaft may be, for example, a throttle signal transmitted to the power shaft by the flight control. The energy system of the unmanned aerial vehicle may be, for example, a device for providing electrical energy, such as a battery of the unmanned aerial vehicle.
In the embodiment of the application, the efficiency of the power system of the unmanned aerial vehicle can be determined according to the environmental information and/or the flight state information of the unmanned aerial vehicle, for example, the environmental information and the flight state information are fused. Because the efficiency of the power system may change under the condition that the power system is abnormal, according to the efficiency of the power system, whether the power system is abnormal or not can be effectively detected, so that fault investigation is timely carried out after the power system is abnormal, and the safety of the unmanned aerial vehicle is ensured.
In some embodiments, in step 120, the efficiency of the power system may be calculated based on an extended kalman filter (extended Kalman flter, EKF) algorithm from the flight information of the drone. The efficiency of the power system may also be simply referred to as power efficiency.
The extended kalman filter algorithm is an extension of the standard kalman filter algorithm in the case of nonlinearities. By using the extended Kalman filter to fuse and update the flight information of the unmanned aerial vehicle, the efficiency of the power system of the unmanned aerial vehicle can be accurately calculated and estimated.
For example, according to the flight state information, based on an EKF algorithm, an optimal estimated value corresponding to the flight state information can be obtained; and information fusion is carried out on the optimal estimated values of the environment information and the flight state information, so that the efficiency of the power system is obtained.
Because the noise of the sensor in the unmanned aerial vehicle is large, the information fusion of the environment information and the flight state information cannot be directly carried out so as to calculate the efficiency of the power system. The corresponding optimal estimated value can be obtained after the flight state information is subjected to EKF processing, and the optimal estimated value of the flight state information and the environmental information are subjected to information fusion, so that the efficiency of the power system can be accurately obtained.
Under the condition that the power system is abnormal, the power consumption of the power system may change, so that a difference exists between the power consumption of the power system and the power consumption of the power system estimated in theory, and whether the power system is abnormal or not can be judged based on the difference.
In particular, in the case of normal flight of the unmanned aerial vehicle, the power consumption of the power system may be equal to or within an acceptable range from the theoretically estimated power consumption of the power system. Under the condition that the power system is abnormal, the power consumption of the power system is higher so as to meet the current normal flight requirement. At this time, some of the total power consumption of the power system is effective power consumption for maintaining normal flight, and the other part is additional power consumption for overcoming the abnormality of the power system. Thus, the efficiency of the power system may be represented by its power consumption.
For example, the ratio between the theoretical power consumption and the actual power consumption of the unmanned aerial vehicle 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 unmanned aerial vehicle in the current state is smaller than the threshold K1, it is determined that the power system is abnormal.
For another example, the actual power consumption of the drone in the current state may be employed 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 unmanned aerial vehicle in the current state is greater than the threshold K2, it is determined that the power system is abnormal.
K1 and K2 may be power consumption values calculated based on theory, for example. K1 may be equal to 1, i.e., as long as the ratio between the theoretical power consumption and the actual power consumption is not equal to 1, the power system is considered to be abnormal. However, in practical applications, K1 is generally set to be 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 degree K1, so that the power system is considered to be abnormal.
As an example, assuming that k1=0.8, the theoretical power consumption of the power system is 6KW, the current actual power consumption of the power system is 10KW, and the ratio between the theoretical power consumption and the actual power consumption is 0.6, since 0.6 is smaller than 0.8, it can be considered that the power system is abnormal.
Similarly, K2 may be equal to 0, i.e., as long as the actual power consumption is not equal to the theoretical power consumption, the power system is considered to be malfunctioning. However, in practical applications, K2 is generally set to be greater than 0, that is, the difference between the theoretical power consumption and the actual power consumption of the power system exceeds the tolerable degree K2, so that the power system is considered to be abnormal.
As an example, assuming that k2=2 KW, the theoretical power consumption of the power system is 6KW, and the current actual power consumption of the power system is 10KW, the difference between the theoretical power consumption and the actual power consumption thereof is 4KW, and since 4KW is greater than 2KW, it can be considered that the power system is abnormal.
The power consumption of the power system is related to the weight of the unmanned aerial vehicle mounted in addition to the environmental information and the flight state information, for example, the relationship between the load of the unmanned aerial vehicle and the power consumption of the power system of the unmanned aerial vehicle is shown in table one, and when the load of the unmanned aerial vehicle is X1, the power consumption of the power system is W1; when the load of the unmanned aerial vehicle is X2, the power consumption of the power system is W2; … …; when the load of the unmanned aerial vehicle is Xn, the power consumption of the power system is Wn. Wherein, the load X1 is more than X2 and more than … … and less than Xn, and the corresponding power consumption W1 is more than W2 and less than … … and less than Wn. That is, the greater the payload of the drone, the greater the power consumption of the power system.
List one
It is appreciated that in the event of an abnormality in the power system, such as blade breakage, motor blockage, electrical modulation failure, etc., the efficiency of the power system is reduced. However, there is a case where the current efficiency of the power system calculated based on the current flight information of the power system is improved compared with the theoretical efficiency, and then it may be determined that other problems occur in the operation of the unmanned aerial vehicle, for example, the load on the unmanned aerial vehicle may be reduced, thereby resulting in an increase in the efficiency of the power system. In this case, it is possible to check whether the unmanned aerial vehicle is not loaded with a load of a sufficient weight, or whether the load drops during flight.
As an example, as shown in fig. 2, detecting a power system of an unmanned aerial vehicle, and obtaining environmental information of an environment where the unmanned aerial vehicle is located, that is, parameters of atmosphere, such as temperature, pressure, density, and the like; control signals such as PWM signals, information of the energy system such as voltage and current; flight state information such as flight speed and flight attitude information. And processing flight state information such as linear velocity, angular velocity, attitude parameters and the like based on an EKF algorithm to obtain optimal estimated values corresponding to the linear velocity, the angular velocity, the attitude parameters and the like. And carrying out information fusion calculation on the obtained most estimated value and the environmental information, so as to obtain the power consumption P1 in the actual flight of the unmanned aerial vehicle.
By means of a large amount of actual flight data in normal conditions and based on aerodynamic theory, an optimally estimated theoretical power consumption P2 can be obtained. Alternatively, a power system efficiency reference table may be set, so that the theoretical efficiency of the power system may be obtained by querying the power system efficiency reference table, and the power system efficiency reference table may include, for example, theoretical efficiency values corresponding to different environmental information and flight state information, respectively.
And finally, determining the actual efficiency of the power system according to the P1 and the P2, and judging whether the power system is abnormal according to whether the difference value between the actual efficiency and the theoretical efficiency exceeds a threshold value.
In some embodiments, the method 100 further comprises: and sending information of the efficiency of the power system and/or a result of whether the power system is abnormal or not to a remote controller and a server of the unmanned aerial vehicle. The remote controller and the server can execute corresponding operations based on the information of the efficiency of the power system and/or the result of whether the power system is abnormal or not, so that the probability of risk of the unmanned aerial vehicle is reduced.
The application also provides a device for detecting the power system of the unmanned aerial vehicle, as shown in fig. 3, the device 200 comprises an acquisition module 210 and a processing module 220.
The acquisition module 210 is configured to acquire flight information of the unmanned aerial vehicle, where the flight information includes environmental information of an environment in which the unmanned aerial vehicle is located and/or flight status information of the unmanned aerial vehicle. The processing module 220 is configured to determine efficiency of a power system of the unmanned aerial vehicle according to the flight information, and determine whether an abnormality occurs in the power system according to the efficiency of the power system.
In some embodiments, the environmental information includes at least one of: atmospheric pressure, atmospheric temperature and atmospheric density that unmanned aerial vehicle was located.
In some embodiments, the flight status information includes at least one of: PWM signals of a power shaft of the power system, voltage of an energy system of the unmanned aerial vehicle, current of the energy system, and information of flying speed and flying attitude of the unmanned aerial vehicle.
In some embodiments, the processing module 220 is specifically configured to: and calculating the efficiency of the power system based on an EKF algorithm according to the flight information.
In one possible implementation, the efficiency of the power system is a ratio of theoretical power consumption to actual power consumption of the unmanned aerial vehicle in the current state, and the processing module 220 is specifically configured to: if the ratio of the theoretical power consumption to the actual power consumption is smaller than the threshold value, determining that the power system is abnormal.
In one possible implementation, the efficiency of the power system is the actual power consumption of the unmanned aerial vehicle in the current state, and the processing module 220 is specifically configured to: if the difference value between the actual power consumption and the theoretical power consumption of the unmanned aerial vehicle in the current state is larger than a threshold value, determining that the power system is abnormal.
In some embodiments, the apparatus 200 further includes a sending module 230, where the sending module 230 is configured to send, to a remote controller and a server of the unmanned aerial vehicle, information about efficiency of the power system and/or a result of whether an abnormality occurs in the power system.
It should be appreciated that, for the details of the apparatus 200 for detecting the unmanned aerial vehicle power system, reference may be made to the foregoing description of the method 100 for detecting the unmanned aerial vehicle power system, and for brevity, a detailed description is omitted herein.
The present application also provides an apparatus for detecting a power system of an unmanned aerial vehicle, as shown in fig. 4, where the apparatus 300 includes a processor 310, and the processor 310 is configured to execute computer instructions stored in a memory, so that the apparatus 300 implements the method 100 for detecting a power system of an unmanned aerial vehicle described in any of the embodiments above. Optionally, the device 300 further comprises a memory 320, the memory 320 being for storing a computer program comprising instructions. The processor 310 and the memory 320 may be connected by a bus.
The device 300 may be, for example, a chip mounted on the drone, the chip including a processor and interface circuitry for providing program instructions or data to the processor, the processor for executing the program instructions to implement the method 100 of detecting a drone power system described in any of the embodiments above. The principle and technical effects of the method 100 are similar to those of the method 100, and reference may be made to the foregoing description of the method 100, so that details are not repeated herein for brevity.
The present application also provides a computer readable storage medium comprising computer instructions which, when run on the apparatus 300, cause the apparatus 300 to perform the method 100 of detecting a unmanned power system described in any of the embodiments above. The principle and technical effects of the method 100 are similar to those of the method 100, and reference may be made to the foregoing description of the method 100, so that details are not repeated herein for brevity.
The present application also provides a computer program product comprising computer readable code, or a non-transitory computer readable storage medium carrying computer readable code, that when run in an apparatus 300, the processor 310 in the apparatus 300 performs the method 100 of detecting a drone power system described in any of the embodiments above. The principle and technical effects of the method 100 are similar to those of the method 100, and reference may be made to the foregoing description of the method 100, so that details are not repeated herein for brevity.
It should be noted that, on the premise of no conflict, the embodiments and/or technical features in the embodiments described in the present application may be combined with each other arbitrarily, and the technical solutions obtained after combination should also fall into the protection scope of the present application. Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (18)
1. A method of detecting an unmanned power system, the method comprising:
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.
2. The method of claim 1, wherein the environmental information comprises at least one of:
the unmanned aerial vehicle is located atmospheric pressure, atmospheric temperature and atmospheric density.
3. The method of claim 1, wherein the flight status information comprises at least one of:
the system comprises a Pulse Width Modulation (PWM) signal of a power shaft of the power system, voltage of an energy system of the unmanned aerial vehicle, current of the energy system, and information of flight speed, flight attitude and flight angle of the unmanned aerial vehicle.
4. A method according to any one of claims 1 to 3, wherein said determining the efficiency of the power system of the unmanned aerial vehicle from the flight information comprises:
and calculating the efficiency of the power system based on an extended Kalman filter EKF algorithm according to the flight information.
5. The method of claim 4, wherein calculating the efficiency of the powertrain based on an EKF algorithm based on the flight information comprises:
obtaining an optimal estimated value corresponding to the flight state information based on the EKF algorithm according to the flight state information;
and carrying out information fusion on the environment information and the optimal estimated value to obtain the efficiency of the power system.
6. A method according to any one of claims 1 to 3, wherein the efficiency of the power system is the ratio of the theoretical power consumption to the actual power consumption of the unmanned aerial vehicle in the current state,
the determining whether the power system is abnormal according to the efficiency of the power system comprises the following steps:
and if the ratio of the theoretical power consumption to the actual power consumption is smaller than a threshold value, determining that the power system is abnormal.
7. A method according to any one of claims 1 to 3, wherein the efficiency of the power system is the actual power consumption of the unmanned aerial vehicle in the current state,
the determining whether the power system is abnormal according to the efficiency of the power system comprises the following steps:
and if the difference value between the actual power consumption and the theoretical power consumption of the unmanned aerial vehicle in the current state is larger than a threshold value, determining that the power system is abnormal.
8. A method according to any one of claims 1 to 3, further comprising:
and sending information of the efficiency of the power system and/or a result of whether the power system is abnormal or not to a remote controller and a server of the unmanned aerial vehicle.
9. An apparatus for detecting an unmanned power system, the apparatus comprising:
the unmanned aerial vehicle flight information acquisition module is used for 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;
the processing module is used for determining the efficiency of the power system of the unmanned aerial vehicle according to the flight information;
the processing module is also used for determining whether the power system is abnormal according to the efficiency of the power system.
10. The apparatus of claim 9, wherein the environmental information comprises at least one of:
the unmanned aerial vehicle is located atmospheric pressure, atmospheric temperature and atmospheric density.
11. The apparatus of claim 9, wherein the flight status information comprises at least one of:
the system comprises a Pulse Width Modulation (PWM) signal of a power shaft of the power system, voltage of an energy system of the unmanned aerial vehicle, current of the energy system, and information of flight speed, flight attitude and flight angle of the unmanned aerial vehicle.
12. The apparatus according to any one of claims 9 to 11, wherein the processing module is specifically configured to:
and calculating the efficiency of the power system based on an extended Kalman filter EKF algorithm according to the flight information.
13. The apparatus of claim 12, wherein the processing module is specifically configured to:
obtaining an optimal estimated value corresponding to the flight state information based on the EKF algorithm according to the flight state information;
and carrying out information fusion on the environment 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 a ratio of a theoretical power consumption to an actual power consumption of the unmanned aerial vehicle in a current state, and the processing module is specifically configured to:
and if the ratio of the theoretical power consumption to the actual power consumption is smaller than a threshold value, determining that the power system is abnormal.
15. The device according to any one of claims 9 to 11, wherein the efficiency of the power system is the actual power consumption of the unmanned aerial vehicle in the current state,
the processing module is specifically configured to:
and if the difference value between the actual power consumption and the theoretical power consumption of the unmanned aerial vehicle in the current state is larger than a threshold value, determining that the power system is abnormal.
16. The apparatus according to any one of claims 9 to 11, further comprising:
and the sending module is used for sending information of the efficiency of the power system and/or a result of whether the power system is abnormal or not to the remote controller and the server of the unmanned aerial vehicle.
17. An apparatus for detecting an unmanned power system, comprising a processor for executing computer instructions stored in a memory to cause the apparatus to implement the method of any one of claims 1 to 8.
18. A computer readable storage medium for storing a computer program which, when executed by a computing device, causes the computing device to implement the method of any one of claims 1 to 8.
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