Unmanned aerial vehicle endurance time evaluation method, device and equipment and storage medium

Abstract

The invention discloses an unmanned aerial vehicle endurance time evaluation method, device and equipment and a storage medium, and the method comprises the steps: obtaining all index test data of an unmanned aerial vehicle, the index test data comprising endurance time of no-load level flight, full-load level flight, no-load hovering and full-load hovering; distributing the weight of each index test data, and calculating a flight environment correction coefficient; based on the index test data, the weight of the index test data and the flight environment correction coefficient, constructing an unmanned aerial vehicle comprehensive endurance index model; and performing quantitative evaluation on the endurance time of the unmanned aerial vehicle by using the comprehensive endurance index model. According to the invention, the evaluation comprehensiveness can be improved, and the accuracy and reliability of the test result can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle testing, and in particular to a method and device for evaluating the endurance time of an unmanned aerial vehicle, as well as an equipment and a storage medium. BACKGROUND

[0002] The endurance time of an unmanned aerial vehicle is one of the key indicators of its performance, directly affecting the mission execution capability and application range of the unmanned aerial vehicle. However, the existing methods for evaluating the endurance time of an unmanned aerial vehicle have the following main problems: single test mode: traditional methods usually only test a single flight mode (such as flat flight or hovering), and do not comprehensively consider different flight states (such as empty load, full load, flat flight, hovering, etc.) that the unmanned aerial vehicle may encounter in actual tasks. This single test mode results in evaluation results that cannot fully reflect the real endurance capability of the unmanned aerial vehicle, and there is a significant deviation from the actual application scenario. Insufficient quantification of environmental factors: the unmanned aerial vehicle is affected by temperature, wind speed, altitude and other environmental factors in actual flight, and these factors will significantly change its energy consumption characteristics. However, existing technologies often ignore or simplify these environmental variables, lack a scientific environmental correction model, and the test results do not match the actual flight conditions. Strong subjectivity in weight allocation: in the comprehensive evaluation of endurance time, existing methods usually rely on expert experience or fixed weight allocation, and lack a dynamic adjustment mechanism. This strongly subjective method is difficult to adapt to changes in different models or task requirements, reducing the reliability and comparability of the evaluation results.

[0003] Therefore, how to improve the accuracy of the evaluation results is a technical problem that needs to be solved at present. SUMMARY

[0004] The main purpose of the present application is to provide a method and device for evaluating the endurance time of an unmanned aerial vehicle, which can improve the comprehensiveness of the evaluation and also improve the accuracy and reliability of the test results.

[0005] In a first aspect, the present application provides a method for evaluating the endurance time of an unmanned aerial vehicle, wherein the method comprises the following steps: obtaining unmanned aerial vehicle index test data, the index test data including: endurance time of empty flat flight, full flat flight, empty hovering and full hovering; allocating weights for the index test data and calculating a flight environment correction coefficient; constructing an unmanned aerial vehicle comprehensive endurance index model based on the index test data, the weights of the index test data and the flight environment correction coefficient; quantitatively evaluating the endurance time of the unmanned aerial vehicle using the comprehensive endurance index model.

[0006] With the first aspect, as an optional implementation, the environment correction model is established, including: a temperature-endurance correction model, a wind speed-energy consumption model and an altitude-energy consumption model. Based on the established environment correction model, the temperature, the steady flight wind speed, the hovering wind speed and the altitude during flight are corrected. According to the corrected temperature, the steady flight wind speed and the altitude, a steady flight environment correction coefficient is calculated. According to the corrected temperature, the hovering wind speed and the altitude, a hovering environment correction coefficient is calculated.

[0007] With the first aspect, as an optional implementation, the comprehensive endurance index model of the unmanned aerial vehicle is: M=α (Tempty flight Csteady flight environment coefficient Asteady flight precision coefficient)+β (Tfull flight Csteady flight environment coefficient Asteady flight precision coefficient)+γ (Tempty hover Chovering environment coefficient Ahovering precision coefficient)+δ (Tfull hover Chovering environment coefficient Ahovering precision coefficient)+η ((Csteady flight environment coefficient+Chovering environment coefficient) / 2), wherein α, β, γ, δ and η are empty flight weight, full flight weight, empty hover weight, full hover weight and environment correction weight, respectively.

[0008] With the first aspect, as an optional implementation, according to the formula: = max(0, 1-Eflight actual / Eflight allowed), the steady flight precision coefficient is calculated, wherein Eflight actual is the measured steady flight track error value, and Eflight allowed is the set allowed steady flight error value. According to the formula: = max(0, 1-Ehover actual / Ehover allowed), the hovering precision coefficient is calculated, wherein Ehover actual is the measured hovering position drift error value, and Ehover allowed is the set allowed hovering drift error value.

[0009] With the first aspect, as an optional implementation, the unmanned aerial vehicle is tested for steady flight and hovering to obtain the empty steady flight endurance time, the full steady flight endurance time, the empty hovering endurance time and the full hovering endurance time of the unmanned aerial vehicle.

[0010] With the first aspect, as an optional implementation, the analytic hierarchy process (AHP) is used to calculate the weight of each index. The weight of each index is calculated by using the entropy weight method. According to the formula: = (AHP weight + entropy weight method weight) / 2, the weight corresponding to each index is calculated, wherein the weight of each index includes: weight of empty flat flight, weight of full flat flight, weight of empty hovering, and weight of full hovering.

[0011] In combination with the above first aspect, as an optional implementation manner, the comprehensive endurance index model is used to calculate the comprehensive endurance index of the unmanned aerial vehicle. According to the high and low of the comprehensive endurance index, the endurance time of the unmanned aerial vehicle is evaluated.

[0012] In a second aspect, the present application provides an unmanned aerial vehicle endurance time evaluation device, which comprises: An acquisition module is configured to acquire index test data of the unmanned aerial vehicle, wherein the index test data includes endurance time of empty flat flight, full flat flight, empty hovering, and full hovering. A processing module is configured to assign weights of the index test data and calculate a flight environment correction coefficient. A construction module is configured to construct a comprehensive endurance index model of the unmanned aerial vehicle based on the index test data, the weights of the index test data, and the flight environment correction coefficient. An evaluation module is configured to use the comprehensive endurance index model to quantitatively evaluate the endurance time of the unmanned aerial vehicle.

[0013] In a third aspect, the present application further provides an electronic device, which comprises a processor and a memory having computer readable instructions stored thereon, wherein the computer readable instructions are executed by the processor to implement the method of any one of the first aspect.

[0014] In a fourth aspect, the present application further provides a computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions are executed by a computer to implement the method of any one of the first aspect.

[0015] The present application provides an unmanned aerial vehicle endurance time evaluation method, device, equipment, and storage medium, wherein the method comprises the steps of: acquiring index test data of the unmanned aerial vehicle, wherein the index test data includes endurance time of empty flat flight, full flat flight, empty hovering, and full hovering; assigning weights of the index test data and calculating a flight environment correction coefficient; constructing a comprehensive endurance index model of the unmanned aerial vehicle based on the index test data, the weights of the index test data, and the flight environment correction coefficient; and using the comprehensive endurance index model to quantitatively evaluate the endurance time of the unmanned aerial vehicle. The present application can improve the evaluation comprehensiveness, and also improve the accuracy and reliability of the test results.

[0016] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application, as claimed. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and serve to explain the principles of the application.

[0018] Figure 1 A flow chart of a method for evaluating the endurance time of a UAV according to an embodiment of the present application; Figure 2 A schematic diagram of a device for evaluating the endurance time of a UAV according to an embodiment of the present application; Figure 3 A schematic diagram of an electronic device according to an embodiment of the present application; Figure 4 A schematic diagram of a computer-readable program medium according to an embodiment of the present application. DETAILED DESCRIPTION

[0019] The exemplary embodiments will be described hereinafter with reference to the accompanying drawings, in which examples are shown. When the description is made with reference to the drawings, the same or similar components are designated with the same or similar reference numerals, unless otherwise specified, throughout the drawings, in which the same or similar components are largely designated with the same or similar reference numerals. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they only describe example implementations consistent with some aspects of the present application, as detailed in the appended claims.

[0020] In addition, the accompanying drawings are intended to be illustrative only, and are not necessarily drawn to scale. Some of the block diagrams in the drawings are functional entities, which do not necessarily correspond to physically or logically independent entities.

[0021] The embodiments of the present application are further described in detail below with reference to the accompanying drawings.

[0022] Reference Figure 1 , Figure 1 A flow chart of a method for evaluating the endurance time of a UAV according to an embodiment of the present application is shown in FIG. 1. As shown in FIG. 1, the method comprises the steps of: Figure 1 Step S101: obtaining UAV index test data, the index test data comprising: endurance time of empty flat flight, endurance time of full flat flight, endurance time of empty hovering, and endurance time of full hovering.

[0023] Specifically, the UAV is tested for flat flight and hovering to obtain the endurance time of empty flat flight, the endurance time of full flat flight, the endurance time of empty hovering, and the endurance time of full hovering.

[0024] ​For the convenience of understanding, the test is divided into the following four basic modes to ensure the coverage of typical working conditions of the UAV: empty flight test (to evaluate the flight endurance under empty flight), full load flight test (to evaluate the flight endurance under full load flight), empty hovering test (to evaluate the flight endurance under empty hovering), and full load hovering test (to evaluate the flight endurance under full load hovering).

[0025] Each test mode is executed according to the following standardized process: Preparation phase: Ensure that the UAV battery is fully charged (SOC = 100%), and the motor, flight control, and sensor system are self-checked normally.

[0026] Pre-set test route (for flight test, set an elliptical route with a short axis ≥ 200 m; for hovering test, set a fixed hovering point).

[0027] Record environmental parameters (temperature, humidity, air pressure, wind speed, and altitude) and use a weather station for real-time monitoring.

[0028] Execution phase: Flight test: The UAV vertically takes off to a height of 10 m and performs route flight at the recommended cruise speed (or the median value of the speed range) of the manufacturer.

[0029] Record the actual flight path using high-precision RTK-GPS and calculate the flight route deviation (lateral / longitudinal error).

[0030] Hovering test: The UAV vertically takes off to a height of 10 m and maintains stable hovering, and uses RTK-GPS / optical flow technology positioning data to record the hovering position drift amount.

[0031] Termination condition: When the battery level drops to the low battery warning threshold (e.g., 10%), terminate the timing and record the endurance time (T).

[0032] If the UAV has an abnormality (e.g., motor overheating, positioning loss), terminate the test and record the abnormal data.

[0033] Repeat the test Each test mode is repeated 5 times to ensure data reliability.

[0034] Each test is separated by ≥ 30 minutes to ensure that the battery is cooled to the ambient temperature before recharging.

[0035] Among them, the key data collection is shown in Table 1.

[0036] Table 1

[0037] Wherein, T empty flat flying: empty flat flying endurance time, take 5 test average or minimum value, unit min (> 0). T full flat flying: full flat flying endurance time, take 5 test average or minimum value, unit min (> 0). T empty hovering: empty hovering endurance time, take 5 test average or minimum value, unit min (> 0). T full hovering: full hovering endurance time, take 5 test average or minimum value, unit min (> 0).

[0038] Step S102: distribute the weight of each index test data, and calculate the flight environment correction coefficient.

[0039] Specifically, the weight of each index is calculated by using the analytic hierarchy process AHP; The weight of each index is calculated by using the entropy weight method; According to the formula: = (AHP weight + entropy weight method weight) / 2, the weight corresponding to each index is calculated, wherein the weight of each index includes: empty flat flying weight, full flat flying weight, empty hovering weight and full hovering weight, The weight of the first index.

[0040] The weights are dynamically adjusted by using the analytic hierarchy process (AHP) + entropy weight method, and the maximum weight = (AHP weight + entropy weight method weight) / 2, for example: alpha: empty flat flying weight (dimensionless (0.2~0.4)), which is calculated by (AHP weight + entropy weight method weight) / 2 to obtain the empty flat flying weight.

[0041] Optionally, beta: full flat flying weight, AHP + entropy weight method calculation, dimensionless (0.2~0.4). Gamma: empty hovering weight, AHP + entropy weight method calculation, dimensionless (0.1~0.3). Delta: full hovering weight, AHP + entropy weight method calculation, dimensionless (0.1~0.3). Eta: environment correction weight, expert experience setting, dimensionless (0.02~0.1).

[0042] In an embodiment, AHP (expert experience weight): the initial weight is set according to experience (such as empty flat flying accounts for 35%, full flat flying accounts for 25%, empty hovering accounts for 20%, full hovering accounts for 15%, and environment correction accounts for 5%).

[0043] Entropy weight method (data driven weight) Based on historical test data, the information entropy of each index is calculated, and the weight is dynamically adjusted. (Such as according to 5 tests, through the entropy weight method, empty flat flying accounts for 30%, full flat flying accounts for 28%, empty hovering accounts for 18%, full hovering accounts for 20%, and environment correction accounts for 4%).

[0044] Entropy weight method calculation process: : the first test the first test mode raw data (such as the first test of the time of the empty flat flight).

[0045] max( ) the maximum value of the first test mode index in all tests.

[0046] min( ) the minimum value of the first test mode index in all tests.

[0047] 1) Standardized value processing:

[0048] 2) Calculate the specific gravity matrix:

[0049] 3) Calculate the information entropy:

[0050] 4) Calculate the weight:

[0051] Calculate the flight environment correction coefficient, including: Establish an environmental correction model, including: temperature-endurance correction model, wind speed-energy consumption model and altitude-energy consumption model; Based on the established environmental correction model, the temperature, flat flight wind speed, hovering wind speed and altitude during flight are corrected; According to the corrected temperature, flat flight wind speed and altitude, the flat flight environment correction coefficient is calculated; According to the corrected temperature, hovering wind speed and altitude, the hovering environment correction coefficient is calculated.

[0052] For easy understanding, the environmental compensation calculation is illustrated: a temperature-endurance correction table is established (such as 25℃ as the reference, ±3% endurance correction for every ±5℃). A wind speed-energy consumption model is established (such as 10% increase in flat flight energy consumption under 3m / s wind speed). An altitude-energy consumption model is established (such as 8% increase in flat flight energy consumption at 1000m).

[0053] 1) C temperature: according to ±3% correction for every ±5℃, temperature correction coefficient, calculation formula: 1-0.03 | T actual-25 | / 5, dimensionless (0.7~1.3), wherein T actual: environmental temperature, measured by portable weather station, unit ℃ (-20~50).

[0054] 2) C flat flight wind speed: according to the energy consumption increase formula, flat flight wind speed correction coefficient, calculation formula: 1-0.01 , dimensionless (1~2.25), wherein, ​​Level flight: level flight wind speed, anemometer measurement, unit m / s (0~15).

[0055] 3) Chover: hover wind speed, hover wind speed correction coefficient, calculation formula: 1-0.005 , dimensionless (1~1.5), wherein, Hover: hover wind speed, anemometer measurement, unit m / s (0~10).

[0056] 4) Caltitude: altitude correction coefficient, according to 8% correction per 1000 meters, calculation formula: 1-0.08 H / 1000, dimensionless (0.6~1), wherein H: altitude, barometer measurement, unit m (0~5000) Clevel flight environment coefficient = Ctemperature Clevel flight wind speed Caltitude.

[0057] Chover environment coefficient = Ctemperature Chover wind speed Caltitude.

[0058] Step S103: based on the index test data, the weight of the index test data, and the flight environment correction coefficient, constructing a comprehensive endurance index model of the unmanned aerial vehicle.

[0059] The comprehensive endurance index model of the unmanned aerial vehicle is: M=α (Tempty level flight Clevel flight environment coefficient Alevel flight accuracy coefficient)+β (Tfull level flight Clevel flight environment coefficient Alevel flight accuracy coefficient)+γ (Tempty hover Chover environment coefficient Ahover accuracy coefficient)+δ (Tfull hover Chover environment coefficient Ahover accuracy coefficient)+η ((Clevel flight environment coefficient+Chover environment coefficient) / 2), wherein α, β, γ, δ and η are empty level flight weight, full level flight weight, empty hover weight, full hover weight and environment correction weight respectively.

[0060] Wherein, according to the formula: = max(0,1-Elevel flight actual / Elevel flight allowed), calculate the level flight accuracy coefficient, wherein Elevel flight actual is the measured level flight track error value, and Elevel flight allowed is the set allowed level flight error value; According to the formula: = max(0, 1 - Ehover actual / Ehover allowed), where Ehover actual is the measured hover position drift error value, and Ehover allowed is the set allowed hover drift error value.

[0061] Specifically, the A flat flying accuracy coefficient is calculated by the formula: max(0, 1 - Eflat actual / Eflat allowed), dimensionless (0~1), where Eflat actual is the flat flying track error (measured value), GPS track analysis, unit m (≥0), and Eflat allowed is the allowed flat flying error (task set value), unit m (>0).

[0062] The A hover accuracy coefficient is calculated by the formula: max(0, 1 - Ehover actual / Ehover allowed), dimensionless (0~1), where Ehover actual is the hover position drift error (measured value), measured by GPS or positioning system, unit m (≥0), and Ehover allowed is the allowed hover drift error (task set value), unit m (>0).

[0063] Step S104: using the comprehensive endurance index model, the endurance time of the unmanned aerial vehicle is quantitatively evaluated.

[0064] Specifically, the comprehensive endurance index of the unmanned aerial vehicle is calculated by using the comprehensive endurance index model; and the endurance time of the unmanned aerial vehicle is evaluated according to the high or low of the comprehensive endurance index.

[0065] In an embodiment, based on the result output by the model M, a multi-dimensional evaluation report is generated, including: comprehensive endurance index (0-100 points, the higher the score, the stronger the endurance ability), basic endurance data (minimum / average endurance time of each mode), environmental correction analysis (such as high temperature leading to 15% decrease in endurance), optimization suggestions (such as reducing cruise speed to improve endurance by 20%).

[0066] In summary, the application obtains the test data of each index of the unmanned aerial vehicle, introduces the environmental compensation coefficient and the calculated index weight to construct the comprehensive endurance index model of the unmanned aerial vehicle, and evaluates the endurance time of the unmanned aerial vehicle through the constructed endurance evaluation system. The beneficial effects include: the first fusion analysis of the test data of the empty / full flat flight and hovering overcomes the limitation of the traditional single test mode, so that the evaluation result is closer to the actual operation scene of the unmanned aerial vehicle. Through the establishment of the temperature-endurance correction curve, the wind speed-energy consumption matrix and other multi-dimensional environmental correction models, the correlation between the laboratory data and the actual application environment is significantly improved. The mixed weight distribution mechanism combining the entropy weight method and the AHP ensures the objectivity of the data and integrates the field expert knowledge, so that the evaluation result is more scientific and reliable. (That is, the first weighted fusion of four types of test data of flat flight, hovering, empty load and full load improves the comprehensiveness of evaluation, establishes the quantitative correction model of temperature, wind speed and altitude, improves the accuracy of test results, and combines AHP (expert experience) and entropy weight method (data driven) to make the evaluation more objective) Referring to Figure 2 , Figure 2 Figure 1 shows a schematic diagram of a device for evaluating the endurance time of an unmanned aerial vehicle provided by the application, as shown in Figure 2 The device comprises: An acquisition module 201 for acquiring test data of each index of the unmanned aerial vehicle, wherein the index test data includes the endurance time of empty flat flight, full flat flight, empty hovering and full hovering.

[0067] A processing module 202 for assigning the weight of each index test data and calculating the flight environment correction coefficient.

[0068] A construction module 203 for constructing a comprehensive endurance index model of the unmanned aerial vehicle based on the index test data, the weight of the index test data and the flight environment correction coefficient.

[0069] An evaluation module 204 for quantitatively evaluating the endurance time of the unmanned aerial vehicle by using the comprehensive endurance index model.

[0070] Further, in a possible implementation, the processing module is further configured to establish an environmental correction model, which includes a temperature-endurance correction model, a wind speed-energy consumption model and an altitude-energy consumption model; The temperature during flight, flat flight wind speed, hovering wind speed and altitude are corrected based on the established environmental correction model; The flat flight environment correction coefficient is calculated according to the corrected temperature, flat flight wind speed and altitude; The hovering environment correction coefficient is calculated according to the corrected temperature, hovering wind speed and altitude.

[0071] Further, in a possible implementation, the constructing module is further configured to construct the comprehensive endurance index model of the UAV, which is M = a (T empty flight C flight environment coefficient A flight accuracy coefficient) + β (T full flight C flight environment coefficient A flight accuracy coefficient) + γ (T empty hovering C hovering environment coefficient A hovering accuracy coefficient) + δ (T full hovering C hovering environment coefficient A hovering accuracy coefficient) + η ((C flight environment coefficient + C hovering environment coefficient) / 2), where a, β, γ, δ, and η are an empty flight weight, a full flight weight, an empty hovering weight, a full hovering weight, and an environment correction weight, respectively.

[0072] Further, in a possible implementation, the processing module is further configured to calculate the flight accuracy coefficient according to the formula: A flight accuracy coefficient = max(0, 1 - E flight actual / E flight allowed), where E flight actual is a measured flight track error value, and E flight allowed is a set allowed flight error value. According to the formula: A hovering accuracy coefficient = max(0, 1 - E hovering actual / E hovering allowed), where E hovering actual is a measured hovering position drift error value, and E hovering allowed is a set allowed hovering drift error value.

[0073] Further, in a possible implementation, the obtaining module is further configured to perform flight and hovering tests on the UAV to obtain an empty flight endurance time, a full flight endurance time, an empty hovering endurance time, and a full hovering endurance time of the UAV.

[0074] Further, in a possible implementation, the processing module is further configured to calculate the weight of each index by using an analytic hierarchy process (AHP); calculate the weight of each index by using an entropy weight method; According to the formula: = (AHP weight + entropy weight method weight) / 2, calculate the weight of each index, where the weight of each index includes an empty flight weight, a full flight weight, an empty hovering weight, and a full hovering weight.

[0075] Further, in a possible implementation, the evaluation module is further configured to calculate a comprehensive endurance index of the UAV by using the comprehensive endurance index model. According to the high or low of the comprehensive endurance index, the endurance time of the UAV is evaluated.

[0076] The electronic device 300 according to this embodiment of the present application will be described below with reference to Figure 3 Figure 3 The electronic device 300 shown is merely an example and should not limit the function and scope of use of the embodiments of the present application.

[0077] As Figure 3 shown, the electronic device 300 is in the form of a general computing device. The components of the electronic device 300 can include, but are not limited to, the at least one processing unit 310 described above, the at least one storage unit 320 described above, and a bus 330 that connects the different system components, including the storage unit 320 and the processing unit 310.

[0078] The storage unit stores program codes that can be executed by the processing unit 310, so that the processing unit 310 performs the steps according to various exemplary embodiments of the present application described in the "Embodiment Method" section of the present specification.

[0079] The storage unit 320 can include a readable medium in the form of a volatile storage unit, such as a random access memory (RAM) 321 and / or a cache memory 322, and can further include a read-only memory (ROM) 323.

[0080] The storage unit 320 can further include program / utility 324 having a set of the program modules 325, including but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which can include implementation of a network environment, or some combination thereof.

[0081] The bus 330 can represent one or more of several types of bus structures, including a storage unit bus or storage unit controller, a peripheral bus, a graphics acceleration port, a processing unit bus, or a local bus using any of a variety of bus architectures.

[0082] ​The electronic device 300 can also communicate with one or more external devices such as a keyboard or a pointing device, a Bluetooth device, etc., and can also communicate with one or more devices that enable a user to interact with the electronic device 300 and / or one or more devices (e.g., a router, a modem, etc.) that enable the electronic device 300 to communicate with one or more other computing devices. Such communication can occur via an input / output (I / O) interface 350. Still yet, the electronic device 300 can communicate with one or more networks such as a local area network (LAN), a wide area network (WAN), and / or the Internet through a network adapter 360. As depicted, the network adapter 360 communicates with the other components of the electronic device 300 via the bus 330. It should be appreciated that the electronic device 300 can be a part of another device or can be a stand-alone device. In addition, the electronic device 300 can be connected to, or a part of, other devices such as a

[0083] Those skilled in the art will readily understand that the example embodiments described herein can be implemented by software and / or by hardware coupled with software, as described above. As such, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (e.g., a CD-ROM, a USB flash drive, a mobile hard disk, or the like) or on a network, and includes a number of instructions for causing a computing device (e.g., a personal computer, a server, a terminal device, or a network device, etc.) to perform the methods according to the embodiments of the present disclosure.

[0084] According to the solutions of the present disclosure, a computer readable storage medium is also provided, which stores the program product capable of implementing the above-mentioned methods. In some possible embodiments, various aspects of the present disclosure can also be implemented in the form of a program product, which includes program codes for causing a terminal device to perform the steps according to various example embodiments of the present disclosure described in the above-mentioned “example method” section when the program product is run on the terminal device.

[0085] Reference Figure 4 As shown, the program product 400 for implementing the above-mentioned methods according to the embodiments of the present disclosure is described, which can take the form of a portable compact disc read-only memory (CD-ROM) and includes program codes, and can be run on a terminal device such as a personal computer. However, the program product of the present disclosure is not limited to this, and in this document, the readable storage medium can be any tangible medium containing or storing a program, which can be used by or in conjunction with an instruction execution system, device, or apparatus.

[0086] The program product can employ any combination of one or more computer-readable media. The computer-readable media can be a computer-readable storage medium or a computer-readable signal medium. The computer-readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include the following: an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0087] The computer-readable signal medium can include a computer-readable storage medium that is propagated as a carrier wave. The computer-readable signal medium can further be any computer-readable medium that is not a storage medium. The computer-readable signal medium can be a computer-readable storage medium that is a propagated signal on a computer-readable storage medium.

[0088] The program code embodied on the computer-readable media can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0089] The program code can be executed by one or more programmable processors, which can be implemented in one or more computer systems. In this context, a computer system generally includes a plurality of these programmable processors, which work in concert to perform a task. Additionally, the program code can be downloaded from an external source, including the internet, through a computer network, or through a broadcast medium.

[0090] Furthermore, the above-described diagrams are merely schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, and are not intended to be limiting. It is readily understood that the processes shown in the above-described diagrams do not indicate or limit the time sequence of the processes. In addition, it is readily understood that the processes can be executed synchronously or asynchronously, for example, in a plurality of modules.

[0091] The foregoing detailed description of the application has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the application to the precise form disclosed, and various modifications and variations are possible in light of the above teachings or can be acquired from practice of the application. The

[0092] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of Figure 1 The flow diagram and / or block diagram in this disclosure can include computer program instructions that can be virtual machine instructions, and / or object code and / or source code, etc. The flow diagram and / or block diagram in this disclosure can also include program instructions that can be platform independent, platform dependent, or a combination of platform independent and platform dependent. Figure 1 The flow diagram and / or block diagram in this disclosure can include computer program instructions that can be virtual machine instructions, and / or object code and / or source code, etc. The flow diagram and / or block diagram in this disclosure can also include program instructions that can be platform independent, platform dependent, or a combination of platform independent and platform dependent.

Claims

1. A method for evaluating the endurance of a drone, characterized in that, include: Acquire test data for various indicators of the drone, including: flight time during empty-load level flight, fully loaded level flight, empty-load hovering, and fully loaded hovering. Assign weights to the test data of each indicator and calculate the flight environment correction coefficient; Based on the aforementioned indicator test data, the weights of the indicator test data, and the flight environment correction coefficient, a comprehensive UAV endurance index model is constructed. The comprehensive endurance index model is used to quantitatively evaluate the flight time of drones.

2. The method according to claim 1, characterized in that, The calculation of the flight environment correction factor includes: An environmental correction model was established, which includes: a temperature-range correction model, a wind speed-energy consumption model, and an altitude-energy consumption model; Based on the established environmental correction model, the temperature, level flight wind speed, hovering wind speed and altitude during flight are corrected. The correction factor for the level flight environment is calculated based on the corrected temperature, level flight wind speed, and altitude. The hovering environment correction factor is calculated based on the corrected temperature, hovering wind speed, and altitude.

3. The method according to claim 1, characterized in that, The construction of the comprehensive drone endurance index model based on the test data of the aforementioned indicators, the weights of the indicators, and the flight environment correction coefficients includes: The comprehensive endurance index model for the drone is: M=α (T empty level flight) C. Level Flight Environment Coefficient A (level flight accuracy coefficient) + β (T fully loaded level flight) C. Level Flight Environment Coefficient A (level flight accuracy coefficient) + γ (T-unloaded hovering) C Hovering Environment Coefficient A (hovering accuracy coefficient) + δ (T fully loaded hovering) C Hovering Environment Coefficient A(hovering accuracy coefficient) + η ((C level flight environment coefficient + C hovering environment coefficient) / 2), where α, β, γ, δ and η are the weights for level flight when unloaded, level flight when fully loaded, hovering when unloaded, hovering when fully loaded and environmental correction weights, respectively.

4. The method according to claim 3, characterized in that, include: According to the formula: =max(0,1-E_actual_level_flight / E_allowable_level_flight), calculates the level flight accuracy coefficient, where E_actual_level_flight is the measured level flight track error value, and E_allowable_level_flight is the set allowable level flight error value. According to the formula: =max(0,1–E_hover_actual / E_hover_allowed), calculates the hovering accuracy coefficient, where E_hover_actual is the measured hovering position drift error value, and E_hover_allowed is the set allowable hovering drift error value.

5. The method according to claim 1, characterized in that, The acquisition of test data for various indicators of the drone includes: The drone was tested for level flight and hovering to obtain its unloaded level flight endurance, fully loaded level flight endurance, unloaded hovering endurance, and fully loaded hovering endurance.

6. The method according to claim 1, characterized in that, The allocation of weights for the test data of each indicator includes: The weight of each indicator is calculated using the Analytic Hierarchy Process (AHP). The weight of each indicator is calculated using the entropy weight method. According to the formula: = (AHP weight + Entropy weight) / 2, calculate the weight corresponding to each indicator, where the weight of each indicator includes: empty level flight weight, fully loaded level flight weight, empty hovering weight, and fully loaded hovering weight.

7. The method according to claim 1, characterized in that, The quantitative evaluation of the drone's flight time using the comprehensive endurance index model includes: Using the aforementioned comprehensive endurance index model, the comprehensive endurance index of the drone is calculated; The drone's flight time is assessed based on the overall flight endurance index.

8. A device for evaluating the endurance of a drone, characterized in that, include: The acquisition module is used to acquire test data of various indicators of the UAV, including: flight time during empty-load level flight, full-load level flight, empty-load hovering and full-load hovering. The processing module is used to assign weights to the test data of each indicator and calculate the flight environment correction coefficient. The construction module is used to construct a comprehensive endurance index model for unmanned aerial vehicles based on the indicator test data, the weights of the indicator test data, and the flight environment correction coefficient. The evaluation module is used to quantitatively evaluate the drone's flight time using the comprehensive endurance index model.

9. An electronic device, characterized in that, The electronic device includes: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer program instructions that, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 7.

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