Method, apparatus, storage medium and electronic device for determining design parameters of unmanned aerial vehicle

Abstract

The present disclosure provides a method, an apparatus, a storage medium, and an electronic device for determining design parameters of a solar-powered unmanned aerial vehicle. The method includes: obtaining wind field data at the location where the unmanned aerial vehicle flies; based on the wind field data, combining the relationships of energy balance, power balance, and weight balance and the flight dynamics equations, significantly relaxing the design constraints, and determining the design parameters of the unmanned aerial vehicle, where the design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, and flight performance parameters. The method in the embodiments of the present disclosure reduces the risk of the solar-powered unmanned aerial vehicle retreating due to the influence of the wind field, and at the same time, the obtained body size and weight are minimized, improving the practicability of the design result.

Description

Technical Field

[0001] The present disclosure relates to the technical field of unmanned aerial vehicles, and particularly to a method, device, computer program product, non-transitory computer-readable storage medium, electronic device, and unmanned aerial vehicle for determining design parameters of an unmanned aerial vehicle. Background Art

[0002] A solar-powered unmanned aerial vehicle is a pure electric aircraft that uses solar energy as the sole energy source. During the day, it uses the solar cell array laid on the wings to absorb solar energy, and after converting it into electrical energy, part of it is used for the flight of the unmanned aerial vehicle, and part is used to charge the energy storage battery. At night, it relies on the energy storage battery to supply power to support the flight. In this way, it cycles day and night to maintain energy balance. The solar-powered unmanned aerial vehicle has the characteristics of long flight time (the flight endurance can reach dozens of days or more) and high flight altitude. These technical characteristics enable the solar-powered unmanned aerial vehicle to achieve many uses of satellites and is an ideal aerial information platform.

[0003] There are significant differences between solar-powered unmanned aerial vehicles and conventional aircraft in terms of usage mode, flight environment, working principle, etc. Therefore, the design parameter design method is also different from that of conventional aircraft. The known representative design methods of solar-powered unmanned aerial vehicles can be found in patents CN108216679A and CN117416520A. The above methods only consider achieving multi-day long-endurance cross-day-and-night flight based on energy balance, and do not consider the practical problems brought by the wind field during flight. There may be a situation where the unmanned aerial vehicle flies out of the mission area due to the cruise speed being less than the wind speed, resulting in mission failure.

[0004] Therefore, it is necessary to propose a new technical solution to solve at least one of the above technical problems. Summary of the Invention

[0005] In order to overcome at least one aspect of the technical problems in the prior art, the present disclosure is proposed.

[0006] According to one aspect of an embodiment of the present disclosure, a method for determining design parameters of an unmanned aerial vehicle is proposed, including: obtaining wind field data at the location where the unmanned aerial vehicle is flying; based on the wind field data, determining the design parameters of the unmanned aerial vehicle, where the design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, power characteristic parameters, and flight performance parameters.

[0007] According to another aspect of an embodiment of the present disclosure, a wind field data acquisition module is proposed for obtaining wind field data at the location where the unmanned aerial vehicle is flying; a design parameter determination module is used to determine the design parameters of the unmanned aerial vehicle based on the wind field data, where the design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, power characteristic parameters, and flight performance parameters.

[0008] According to another aspect of an embodiment of the present disclosure, there is provided a computer program product including program code instructions which, when the program product is executed by a computer, cause the computer to execute the method according to the first aspect of the embodiment of the present disclosure.

[0009] According to another aspect of an embodiment of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the method according to the first aspect of the embodiment of the present disclosure.

[0010] According to another aspect of an embodiment of the present disclosure, there is provided an electronic device including: a processor, a memory in electronic communication with the processor; and instructions stored in the memory and executable by the processor to cause the electronic device to execute the method according to the first aspect of the embodiment of the present disclosure.

[0011] According to another aspect of an embodiment of the present disclosure, there is provided an unmanned aerial vehicle (UAV), the design parameters of which are obtained based on the method according to the first aspect of the embodiment of the present disclosure. Description of the Drawings

[0012] The above and other aspects and features of the present disclosure will be clearly presented from the following description of embodiments in conjunction with the drawings, where:

[0013] Figure 1 is a flowchart of a method for determining design parameters of an unmanned aerial vehicle according to an embodiment of the present disclosure;

[0014] Figure 2 is a schematic diagram of a reference wind speed - altitude curve and a flight speed - flight altitude curve according to an embodiment of the present disclosure;

[0015] Figure 3 is a schematic diagram of the energy balance principle of an unmanned aerial vehicle according to an embodiment of the present disclosure;

[0016] Figure 4 is a flowchart of a specific example of a method for determining design parameters of an unmanned aerial vehicle according to an embodiment of the present disclosure;

[0017] Figure 5 is a schematic block diagram of a device for determining design parameters of an unmanned aerial vehicle according to an embodiment of the present disclosure. Detailed Embodiments

[0018] The following description of the embodiments of the present disclosure with reference to the drawings is intended to explain the general inventive concept of the present disclosure and should not be construed as a limitation to the present disclosure. All other embodiments obtained by those skilled in the art based on the embodiments in the present disclosure fall within the scope of protection of the present disclosure.

[0019] The overall design of the unmanned aerial vehicle (UAV) is a process of knowing the design requirements, solving for the design parameters, and determining the overall UAV scheme. In the embodiments of the present disclosure, the design parameters of the UAV include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, power characteristic parameters, and flight performance parameters. In some embodiments of the present disclosure, the wing loading and wing area of the UAV are taken as the design parameters of primary concern. In some embodiments of the present disclosure, the designed UAV is a solar UAV.

[0020] A flight profile is used to describe the flight path of an aircraft for a specific mission. Exemplarily, the flight profile of a solar UAV within one day and night (i.e., a single cycle period) is as follows: at night, the UAV cruises at a fixed altitude; during the day, as the sun rises, the UAV climbs from the above-mentioned fixed altitude, maintains cruising after climbing a certain altitude (i.e., the ceiling altitude), and as the sun sets, the UAV descends from a high altitude until it returns to the above-mentioned fixed altitude. In some embodiments of the present disclosure, when determining the design parameters based on the single-cycle flight profile, the UAV is regarded as flying at a fixed altitude, that is, the UAV always maintains a fixed flight altitude within one day and night.

[0021] The embodiments of the present disclosure provide a method for determining the design parameters of a UAV, including: obtaining wind field data at the location where the UAV is flying; based on the wind field data, determining the design parameters of the UAV, where the design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, and power characteristic parameters. In some embodiments of the present disclosure, the location where the UAV is flying may refer to the latitude of the mission area of the UAV. As will be mentioned below, the step of "determining the design parameters of the UAV based on the wind field data" can be implemented in the manner of step 130 and step 140, and can also be implemented in other ways, for example, replacing the "night flight altitude" in Patent CN108216679A with the minimum over-night altitude considering the influence of the wind field in the present disclosure to obtain the corresponding design parameters.

[0022] In an alternative embodiment, the step of "obtaining wind field data at the location where the UAV is flying" may further include: obtaining the mission design objectives of the UAV, where the mission design objectives include mission latitude and mission date; based on the mission latitude and mission date, determining the wind field data at the location where the UAV is flying.

[0023] In an alternative embodiment, the step of "determining the design parameters of the UAV based on the wind field data" may further include: based on the wind field data, determining the minimum over-night altitude of the UAV; based on the minimum over-night altitude of the UAV, determining the design parameters of the UAV. The meaning of the "minimum over-night altitude" will be described in detail below.

[0024] Figure 1A flowchart of a method for determining the design parameters of an unmanned aerial vehicle according to an embodiment of the present disclosure.

[0025] As Figure 1 shown, the method includes the following steps:

[0026] Step 110, obtain the mission design objectives of the unmanned aerial vehicle, where the mission design objectives include mission latitude and mission date.

[0027] The mission design objectives of the unmanned aerial vehicle are used to describe the mission design requirements of the unmanned aerial vehicle. In the embodiments of the present disclosure, the mission design objectives include mission latitude and mission date. In addition, the mission design objectives may further include payload weight, payload power consumption, etc.

[0028] Step 120, determine the wind field data at the location where the unmanned aerial vehicle flies according to the mission latitude and mission date.

[0029] The wind field data is used to describe parameters such as wind speed and wind direction in a certain area. Exemplarily, the wind field data at the location where the unmanned aerial vehicle flies can be determined by querying historical statistical data or model prediction according to the mission latitude and mission date.

[0030] Step 130, determine the minimum over-night altitude of the unmanned aerial vehicle according to the wind field data.

[0031] As mentioned above, the unmanned aerial vehicle cruises at a fixed altitude at night. Generally speaking, the higher the altitude, the smaller the air density, and the greater the speed required for cruising. The lower the altitude, the greater the air density, and the smaller the speed required for cruising. Since there is an upper limit to the speed of the unmanned aerial vehicle, there is also an upper limit to the night cruising altitude of the unmanned aerial vehicle. Generally, the maximum altitude of the unmanned aerial vehicle's night cruise is called the over-night altitude.

[0032] In the embodiments of the present disclosure, during the design process of the unmanned aerial vehicle, the influence of the wind field on the practicality of the unmanned aerial vehicle is considered, that is, the flight speed of the unmanned aerial vehicle during night cruise needs to be greater than or equal to the local wind speed. For the typical over-night altitude of the unmanned aerial vehicle, as the altitude increases, the flight speed of the unmanned aerial vehicle increases while the wind speed decreases, and the possibility of retreat flight decreases. Therefore, in the embodiments of the present disclosure, to ensure the practicality of the unmanned aerial vehicle, the minimum over-night altitude of the unmanned aerial vehicle is mainly concerned.

[0033] In an alternative embodiment, step 130 may further include the following steps 131-step 133:

[0034] Step 131, determine the reference wind speed corresponding to the mission design objectives according to the wind field data, where the reference wind speed is the maximum wind speed corresponding to a specific probability, and the reference wind speed changes with height and forms a reference wind speed-height curve.

[0035] In an embodiment of the present disclosure, the maximum wind speed corresponding to a specific probability represents the probability that the actual wind speed does not exceed this wind speed within a certain statistical period (for example, one month) is the above specific probability. The value of the specific probability can be determined according to the actual situation, such as 80% or 90%. As an example, the maximum wind speed with a 90% probability is 10 m / s, which means that the probability that the actual wind speed does not exceed 10 m / s within the statistical period is 90%.

[0036] Optionally, the above specific probability is greater than 50%, which can ensure that the drone will not fly backward for more than half of the time during night flight. It is easy to understand that the greater the value of the above specific probability, the lower the risk of the drone flying backward designed.

[0037] Generally speaking, the wind speeds at different heights are different. Therefore, the above reference wind speed changes with height, and the change relationship between the two can be represented by a reference wind speed-height curve.

[0038] Step 132: Based on the empirical values of the wing load and the lift coefficient, determine the flight speed-flight height curve corresponding to the drone.

[0039] Generally speaking, the expression of the flight speed is as follows:

[0040]

[0041] Among them, V is the flight speed, W_Sw is the wing load of the drone, CL is the lift coefficient, ρ(H) is the atmospheric density at different heights, and H is the flight height.

[0042] In step 132, the empirical value ranges of the wing load and the lift coefficient can be referred to, and the empirical values of the wing load and the lift coefficient that make the flight speed maximum are substituted to obtain the calculation relationship between the flight speed and the flight height, and then the flight speed-flight height curve is obtained.

[0043] Step 133: According to the intersection point of the reference wind speed-height curve and the flight speed-flight height curve, determine the flight height corresponding to the flight speed when the flight speed is equal to the reference wind speed, and obtain the minimum night flight height.

[0044] Here, in combination with Figure 2 An explanation of step 133 is given. See Figure 2, the dashed line in the figure corresponds to the reference wind speed - altitude curve, and the solid line corresponds to the flight speed - flight altitude curve. There are two intersections between the two curves. The intersection below corresponds to a lower altitude and is located in the troposphere, where there are other complex meteorological conditions such as clouds, rain, lightning, etc., which are not conducive to the flight safety of solar - powered unmanned aerial vehicles, so it is discarded. The upper intersection represents that the flight speed is equal to the reference wind speed (here it is the maximum wind speed with an 80% probability), and the corresponding flight altitude is about 17000m. Therefore, the minimum over - night altitude is 17000m. Based on the above - mentioned minimum over - night altitude, if the altitude increases, the flight speed increases while the reference wind speed decreases, and the risk of the unmanned aerial vehicle flying backward is further reduced.

[0045] Step 140, based on the minimum over - night altitude of the unmanned aerial vehicle, determine the design parameters of the unmanned aerial vehicle.

[0046] In the overall design of the unmanned aerial vehicle, the over - night altitude has an impact on the design parameters of the solar - powered unmanned aerial vehicle. In the embodiments of the present disclosure, determining the minimum over - night altitude of the unmanned aerial vehicle based on wind field data and determining the design parameters of the unmanned aerial vehicle based on the minimum over - night altitude of the unmanned aerial vehicle can reduce the risk of the designed unmanned aerial vehicle flying backward due to the influence of the wind field and improve the practicality of the design result.

[0047] The following will exemplarily illustrate the implementation manner of step 140. It should be noted that the implementation manner of step 140 is not limited to the manner described below. The minimum over - night altitude obtained in step 130 can be applied to any known overall design scheme of the unmanned aerial vehicle. For example, the "night flight altitude" in Patent CN108216679A can be replaced with the "minimum over - night altitude" obtained in step 130 to obtain the corresponding overall design result. It is easy to understand that the practicality of the above - mentioned overall design result has been improved.

[0048] In an alternative embodiment, step 140 may further include the following steps 141 - 144:

[0049] Step 141, determine the initial iteration value of the wing loading and the initial iteration value of the wing area of the unmanned aerial vehicle.

[0050] The initial iteration value of the wing loading and the initial iteration value of the wing area of the unmanned aerial vehicle can be determined by random selection or other methods according to the conventional value ranges of the wing loading and the wing area of the unmanned aerial vehicle.

[0051] Step 142, based on the minimum over - night altitude, the initial iteration value of the wing loading, and the initial iteration value of the wing area, combined with the design task objective and design input parameters of the unmanned aerial vehicle, determine the required endurance factor of the unmanned aerial vehicle from the perspective of energy conversion.

[0052] Design input parameters are used to describe the existing design basis. Exemplarily, the design input parameters may include one or more of the weight of on-board equipment, the power consumption of on-board equipment, the conversion efficiency of solar cell modules, the areal density of solar cell modules, the layout ratio of solar cell modules, the efficiency of the energy management system, the energy density of energy storage batteries, the charge and discharge efficiency of energy storage batteries, the depth of discharge of energy storage batteries, the efficiency of the propulsion system, the power-to-weight ratio of the propulsion system, and the structural overload factor.

[0053] The definition formula of the endurance factor is:

[0054]

[0055] Where E is the endurance factor, CL is the lift coefficient, and CD is the drag coefficient. The larger the endurance factor, the smaller the power required for the UAV to fly under the same conditions.

[0056] In an alternative embodiment, step 142 may further include the following steps 142a - 142c:

[0057] Step 142a: Determine the solar energy absorbed by the solar cell module per unit area within a single cycle period according to the minimum over-night altitude, mission latitude, mission date, the conversion efficiency of solar cell modules, and the layout ratio of solar cell modules, in accordance with the solar radiation power model.

[0058] In the present disclosure, a single cycle period refers to a single cross-day-and-night flight cycle.

[0059] In the above step 142a, first, determine the solar vertical irradiation intensity based on the minimum over-night altitude (here it is assumed that the flight altitude of the UAV is fixed within a single cycle period, so the flight altitudes during the day and at night are both the minimum over-night altitude). Secondly, calculate the radiation power of the solar cell module per unit area. Finally, calculate the solar energy absorbed by the solar cell module per unit area within a single cycle period.

[0060] Step 142b: Determine the available flight power per unit wing area according to the solar energy absorbed by the solar cell module per unit area within a single cycle period and the charge and discharge efficiency of the energy storage battery, in accordance with the energy balance model.

[0061] Figure 3 is a schematic diagram of the UAV energy balance principle according to an embodiment of the present disclosure. Refer to Figure 3 , Figure 3 In, the horizontal axis represents the time change within a single cycle period, and the vertical axis represents power. Among them, the parabola represents the change in the power of the UAV absorbing solar energy over time, and the straight line represents the change in the power consumed by the UAV over time. Figure 3Among them, region B1 and B2 represent the energy consumed by the drone during night flight, region C represents the energy consumed by the drone during day flight, and region A represents the remaining energy during the day that can be used to store in the energy storage battery. Based on this energy balance principle, the following quantitative relationship exists:

[0062]

[0063] Wherein, P tot is the available flight power per unit wing area, P sun is the solar energy absorption power per unit wing, η c is the charge and discharge efficiency of the energy storage battery, t1 is the sunrise time, and t2 is the sunset time.

[0064] Based on the above, the available flight power per unit wing area can be obtained.

[0065] Step 142c: According to the minimum over-night height, the available flight power per unit wing area, the initial value of wing loading iteration, the initial value of wing area iteration, the load power consumption, and the propulsion system efficiency, determine the required endurance factor of the drone according to the flight required power model.

[0066] In the above step 142c, first, calculate the required propulsion power for the drone flight according to the minimum over-night height, the propulsion system efficiency, the initial value of wing loading iteration, and the initial value of wing area iteration. Secondly, calculate the required power for the drone flight according to the required propulsion power for the drone flight, the power consumption of on-board equipment, and the load power consumption. Finally, determine the required endurance factor of the drone according to the available flight power per unit wing area and the required power for the drone flight. The above calculation process can be implemented in a manner known to those skilled in the art.

[0067] Step 143: Based on the minimum over-night height, the initial value of wing loading iteration, and the initial value of wing area iteration, combined with the design mission objective and design input parameters of the drone, determine the design endurance factor of the drone from the perspective of aerodynamic characteristics.

[0068] In an alternative embodiment, step 143 may further include the following steps 143a-143c:

[0069] Step 143a: According to the minimum over-night height, the initial value of wing loading iteration, and the initial value of wing area iteration, determine the weight per unit wing area of each subsystem, and determine the structural weight per unit wing area according to the weight model.

[0070] The weight per unit wing area of each of the above subsystems includes, for example, any one or more of the propulsion system weight per unit wing area, the solar cell module weight per unit wing area, the energy storage battery weight per unit wing area, the on-board equipment weight per unit wing area, and the load weight per unit wing area.

[0071] Step 143b: Determine the external dimension parameters of the UAV according to the structural weight per unit wing area and the UAV size model.

[0072] The above-mentioned external dimension parameters of the UAV include, for example, data such as the aspect ratio and / or wingspan of the UAV.

[0073] Step 143c: Determine the design endurance factor of the UAV based on the external dimension parameters of the UAV and the empirical formula of the UAV drag coefficient.

[0074] The empirical formula of the UAV drag coefficient is as follows:

[0075] CD = CD 0w + CD 0t + CD 0p + CD 0b +(1 + δ) / (πAR)CL 2

[0076] Where, CD 0w is the zero-lift drag coefficient of the wing, CD 0t is the drag coefficient of the vertical tail, CD 0p is the drag coefficient of the landing gear, CD 0b is the drag coefficient of the pod and other exposed components, (1 + δ) / (πAR)CL 2 is the induced drag of the wing. Based on this, the maximum endurance factor and its corresponding lift coefficient can be calculated. The above-mentioned maximum endurance factor is the design endurance factor of the UAV. The above-mentioned lift coefficient is the design lift coefficient which will be mentioned below.

[0077] Step 144: Compare the required endurance factor with the design endurance factor to determine whether the initial iteration value of the wing area meets the requirements.

[0078] If the design endurance factor is greater than or close to the required endurance factor, the initial iteration value of the wing area meets the requirements.

[0079] In an optional embodiment, step 140 further includes the following steps:

[0080] Step 145: Determine the maximum lift coefficient of the UAV according to the reference wind speed, the minimum over-night height, and the initial iteration value of the wing loading.

[0081] The calculation formula of the maximum lift coefficient is as follows:

[0082]

[0083] Where, CL wind is the maximum lift coefficient, is the initial iteration value of the wing loading, ρ is the atmospheric density at the minimum over-night height, Vwind is the reference wind speed, and g is the acceleration due to gravity.

[0084] Step 146: Based on the minimum overnight altitude, the initial iteration value of wing loading, and the initial iteration value of wing area, combined with the design mission objective and design input parameters of the unmanned aerial vehicle (UAV), determine the design lift coefficient of the UAV from the perspective of aerodynamic characteristics.

[0085] The execution process of Step 146 can refer to Step 143, where the design lift coefficient is obtained in Step 143c.

[0086] Step 147: Compare the maximum lift coefficient with the design lift coefficient to determine whether the initial iteration value of wing area meets the requirements.

[0087] In an alternative embodiment, Step 140 further includes the following steps:

[0088] Step 148: Based on the minimum overnight altitude, the initial iteration value of wing loading, and the initial iteration value of wing area, combined with the design mission objective and design input parameters of the UAV, determine the design dimension parameters of the UAV from the perspective of aerodynamic characteristics.

[0089] The above-mentioned shape dimension parameters of the UAV, for example, include data such as the aspect ratio and / or wingspan of the UAV.

[0090] Step 145 can be combined with Step 143b into the same step.

[0091] Step 149: Compare the design dimension parameters of the UAV with the empirical range of dimension parameters to determine whether the initial iteration value of wing loading meets the requirements.

[0092] If the design dimension parameters of the UAV fall within the empirical range of dimension parameters, the initial iteration value of wing loading meets the requirements.

[0093] In an alternative embodiment, Step 140 further includes: when the initial iteration value of wing area does not meet the requirements, re-obtain the initial iteration value of wing area; and / or when the initial iteration value of wing loading does not meet the requirements, re-obtain the initial iteration value of wing loading.

[0094] In the above-mentioned embodiment, Step 140 is carried out in a cyclic iteration manner until the wing area and wing loading that meet the requirements are obtained.

[0095] In the above-mentioned embodiment, the design parameters of the UAV are the design parameters under single-cycle and constant-altitude flight. On this basis, a multi-cycle and variable-altitude flight calculation model can be established, and the multi-cycle and variable-altitude flight calculation model can be optimized to obtain the final design parameters of the UAV.

[0096] In the multi-cycle, variable-altitude flight calculation model, the required propulsion power for the three stages of climbing, descending, and cruising of a solar-powered unmanned aerial vehicle (UAV) can be calculated respectively based on the power balance principle and flight dynamics. According to the relationship between the solar radiation power and the required power (the sum of the required propulsion power, payload power, and on-board equipment power consumption) at each moment, the flight state of the UAV can be judged, and at the same time, the charge-discharge energy balance of the energy storage battery can be achieved, ultimately achieving the goal of multi-day day-night cycle flight.

[0097] In an alternative embodiment, in the step of optimizing the multi-cycle, variable-altitude flight calculation model, the optimized variables are the layout rate of the solar cell modules and the weight of the energy storage battery, and the optimization result is to minimize the weight of the UAV.

[0098] Exemplarily, the mathematical expression of the optimization problem is as follows:

[0099] Variables: η asc , W c

[0100] Objective function: W tot = f(η asc , W c ) = q sc S W η asc + W c + W else

[0101] Subject to the condition: g(η asc , W c ) = 14 - n(η asc , W c ) ≤ 0

[0102] Where η asc is the layout rate of the solar cell modules, W c is the weight of the energy storage battery, q sc is the surface density of the solar cell modules, S W is the wing area, W else is the weight of other components except the energy system, and n(η asc , W c ) is the number of available cycles calculated according to the multi-day day-night cycle flight calculation model. Without loss of generality, it is considered that meeting the energy balance for more than 14 days has a certain practicality.

[0103] The optimization model is Where X = [η asc , W c

[0104] Through the above optimization process, the total weight of the UAV can be further reduced, which is beneficial to further improving the practicality of the UAV.

[0105] Figure 4 It is a flowchart of a specific example of a method for determining the design parameters of an unmanned aerial vehicle according to an embodiment of the present disclosure. As Figure 4 shown, the implementation process of this example is as follows:

[0106] (1) Determine the design task objectives and design input parameters of the unmanned aerial vehicle, and determine the practical minimum over-night altitude and its corresponding reference wind speed according to the wind field data;

[0107] (2) Given the initial iteration values of the unmanned aerial vehicle, including the wing loading Wtot_Sw0 and the wing area Sw0 of the unmanned aerial vehicle;

[0108] (3) According to the design input parameters and design task objectives of the unmanned aerial vehicle determined in step (1), combined with the energy balance model, the solar radiation power model and the flight required power model, calculate the required endurance factor E corresponding to the given design task objective 需 ;

[0109] (4) According to the design input parameters and design task objectives of the unmanned aerial vehicle determined in step (1), combined with the size and weight model, calculate the weight and external dimension parameters of each component corresponding to the given wing loading and wing area; combined with the aerodynamic characteristics model, calculate the corresponding design lift coefficient Cl of the unmanned aerial vehicle and the endurance factor E 设 ;

[0110] (5) Calculate the maximum lift coefficient according to the reference wind speed obtained in step (1) and the wing loading of the unmanned aerial vehicle given in step (2);

[0111] (6) Calculate the required endurance factor E obtained in step (3) 需 and the deviation between the design endurance factor E obtained in step (4) 设 . If the deviation is close to 0, and at the same time the design lift coefficient calculated in step (4) is less than the maximum lift coefficient obtained in step (5), then go to step (7), otherwise return to step (2) and update the initial value of the wing area Sw0 of the unmanned aerial vehicle;

[0112] (7) According to the size parameters of the unmanned aerial vehicle corresponding to the aerodynamic characteristics that meet the deviation in step (6), calculate whether the aspect ratio AR of the unmanned aerial vehicle exceeds the constraint. If it does not exceed the design constraint, then go to step (8), otherwise return to step (2) and update the initial value of the wing loading Wtot_Sw0 of the unmanned aerial vehicle;

[0113] (8) According to the weight and external dimension parameters of each component obtained in the above steps, establish a multi-cycle, variable altitude flight calculation model, optimize the energy system parameters, and finally complete the determination of the design parameters of the practical solar unmanned aerial vehicle with minimized size and weight.

[0114] In Figure 4In the example shown, by determining the wing loading and wing area of the UAV based on an iterative loop method, the minimum wing area that meets the requirements of the endurance factor and lift coefficient can be obtained, which can avoid waste of the wing area, is beneficial to reducing the size of the UAV, and further improves the practicality of the UAV.

[0115] The following provides a specific example to further illustrate the implementation process of the method in the present disclosure:

[0116] A certain solar UAV carries a 20 kg and 500 W load to perform tasks between the spring and autumn equinoxes south of 40° north latitude. It is expected that the weight of the on-board equipment is 30 kg, the power consumption of the on-board equipment is 300 W, the conversion efficiency of the solar cell module is 30%, the surface density of the solar cell module is 0.6 kg / m2, the patch rate of the solar cell module is 70%, the efficiency of the energy manager is 95%, the energy density of the energy storage battery is 400 Wh / kg, the charge and discharge efficiency of the energy storage battery is 98%, the depth of discharge of the energy storage battery is 90%, the power-to-weight ratio of the propulsion system is 400 W / kg, and the efficiency of the propulsion system is 72%. According to the above design input parameters, the design parameters such as the weight and shape of the UAV are determined by using the design parameter design method of the present invention.

[0117] Select the weakest solar irradiance day within the mission range (40° north latitude, autumn equinox (September 22nd)) as the design point. According to the design parameter design method of the present invention, release the constraints on the external dimensions. First, according to the historical wind field data in the target area, determine that the minimum practical over-night altitude is 16.9 km. To store energy using gravitational potential energy, the ceiling altitude is set to 28 km. The practical UAV design parameters calculated are as follows:

[0118] Select the weakest solar irradiance day within the mission range (40° north latitude, autumn equinox (September 22nd)) as the design point. According to the method for determining the design parameters provided in the present disclosure, release the constraints on the external dimensions. First, according to the historical wind field data in the target area, determine that the minimum practical over-night altitude is 16.9 km. To store energy using gravitational potential energy, the ceiling altitude is set to 28 km. The practical UAV design parameters calculated are as follows:

[0119]

[0120]

[0121] If practicality is not considered and the over-night altitude is set relatively low, only 12 km, the cruise speed is much less than the wind speed at 12 km altitude. There is a flight safety risk and a phenomenon of flying backward will occur, and the mission cannot be executed. In addition, if the external dimensions such as the fuselage length, horizontal tail moment arm, and vertical tail moment arm of the UAV are restricted, the total takeoff weight of the determined UAV is 550 kg, and the wing area is 144 m 2 , and the design result is significantly larger than the design result of the present invention, making it difficult to be practical.

[0122] Figure 5 is a schematic block diagram of a device for determining the design parameters of an unmanned aerial vehicle according to an embodiment of the present disclosure. As Figure 5 shown, the device 500 includes: a wind field data acquisition module 510, configured to acquire wind field data at the location where the unmanned aerial vehicle flies; a design parameter determination module 520, configured to determine the design parameters of the unmanned aerial vehicle based on the above-mentioned wind field data, where the above-mentioned design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, and power characteristic parameters.

[0123] It should be understood that Figure 5 each module of the device 500 shown in [[ ]] can correspond to each step in the method described above with reference. Thus, the operations, features, and advantages described above for the method also apply to the device 500 and the modules it includes. For the sake of brevity, some operations, features, and advantages are not described herein again.

[0124] In an alternative embodiment, the wind field data acquisition module 510 further includes: a mission design objective acquisition module 511, configured to acquire the mission design objective of the unmanned aerial vehicle, where the above-mentioned mission design objective includes mission latitude and mission date; a wind field data determination module 512, configured to determine the wind field data corresponding to the above-mentioned mission design objective according to the above-mentioned mission latitude and the above-mentioned mission date.

[0125] In an alternative embodiment, the design parameter determination module 520 further includes: a minimum overnight height determination module 521, configured to determine the minimum overnight height of the above-mentioned unmanned aerial vehicle according to the above-mentioned wind field data; a design parameter determination module 522, configured to determine the design parameters of the above-mentioned unmanned aerial vehicle based on the minimum overnight height of the above-mentioned unmanned aerial vehicle.

[0126] In an alternative embodiment, the minimum overnight height determination module 521 is further configured to: determine the flight height corresponding to the above-mentioned flight speed when the above-mentioned flight speed is equal to the above-mentioned reference wind speed according to the intersection point of the reference wind speed - height curve and the flight speed - flight height curve, and obtain the above-mentioned minimum overnight height, where the above-mentioned reference wind speed is the maximum wind speed corresponding to a specific probability.

[0127] In an alternative embodiment, the above-mentioned reference wind speed - height curve is obtained by the following method: according to the above-mentioned wind field data, determine the reference wind speed corresponding to the above-mentioned mission design objective, and the above-mentioned reference wind speed changes with height to form a reference wind speed - height curve.

[0128] In an alternative embodiment, the above-mentioned flight speed - flight height curve is obtained by the following method: based on the empirical values of wing loading and lift coefficient, determine the flight speed - flight height curve corresponding to the above-mentioned unmanned aerial vehicle

[0129] In an alternative embodiment, the design parameter determination module 522 is further configured to: determine an initial value of wing loading iteration and an initial value of wing area iteration for the above-mentioned unmanned aerial vehicle; based on the above-mentioned minimum over-night altitude, the above-mentioned initial value of wing loading iteration, and the above-mentioned initial value of wing area iteration, in combination with the design task objective and design input parameters of the above-mentioned unmanned aerial vehicle, determine the required endurance factor of the above-mentioned unmanned aerial vehicle from the perspective of energy conversion; based on the above-mentioned minimum over-night altitude, the above-mentioned initial value of wing loading iteration, and the above-mentioned initial value of wing area iteration, in combination with the design task objective and design input parameters of the above-mentioned unmanned aerial vehicle, determine the designed endurance factor of the above-mentioned unmanned aerial vehicle from the perspective of aerodynamic characteristics; compare the above-mentioned required endurance factor with the above-mentioned designed endurance factor to determine whether the above-mentioned initial value of wing area iteration meets the requirements.

[0130] In an alternative embodiment, the design parameter determination module 522 is further configured to: determine the solar energy absorbed by the solar cell module per unit area within a single cycle according to the above-mentioned minimum over-night altitude, the above-mentioned mission latitude, the above-mentioned mission date, the conversion efficiency of the solar cell module, and the sheet ratio of the solar cell module, according to the solar radiation power model; determine the available flight power per unit wing area according to the solar energy absorbed by the solar cell module per unit area within the above-mentioned single cycle and the charge-discharge efficiency of the energy storage battery, according to the energy balance model; determine the required endurance factor of the above-mentioned unmanned aerial vehicle according to the above-mentioned minimum over-night altitude, the above-mentioned available flight power per unit wing area, the above-mentioned initial value of wing loading iteration, the above-mentioned initial value of wing area iteration, the load power consumption, and the propulsion system efficiency, according to the flight required power model.

[0131] In an alternative embodiment, the design parameter determination module 522 is further configured to: determine the weight of each subsystem per unit wing area according to the above-mentioned minimum over-night altitude, the above-mentioned initial value of wing loading iteration, and the above-mentioned initial value of wing area iteration, and determine the structural weight per unit wing area according to the weight model; determine the external dimension parameters of the above-mentioned unmanned aerial vehicle according to the above-mentioned structural weight per unit wing area, according to the unmanned aerial vehicle dimension model; determine the designed endurance factor of the above-mentioned unmanned aerial vehicle based on the external dimension parameters of the above-mentioned unmanned aerial vehicle and the empirical formula of the drag coefficient of the unmanned aerial vehicle.

[0132] In an alternative embodiment, the design parameter determination module 522 is further configured to: determine the maximum lift coefficient of the above-mentioned unmanned aerial vehicle according to the above-mentioned reference wind speed, the above-mentioned minimum over-night altitude, the above-mentioned initial value of wing loading iteration, and the above-mentioned initial value of wing area iteration; based on the above-mentioned minimum over-night altitude, the above-mentioned initial value of wing loading iteration, and the above-mentioned initial value of wing area iteration, in combination with the design task objective and design input parameters of the above-mentioned unmanned aerial vehicle, determine the designed lift coefficient of the above-mentioned unmanned aerial vehicle from the perspective of aerodynamic characteristics; compare the above-mentioned maximum lift coefficient with the above-mentioned designed lift coefficient to determine whether the above-mentioned initial value of wing area iteration meets the requirements.

[0133] In an alternative embodiment, the design parameter determination module 522 is further configured to: based on the above minimum overnight height, the initial value of the wing load iteration, and the initial value of the wing area iteration, and in combination with the design task objective and design input parameters of the above UAV, determine the design dimension parameters of the above UAV from the perspective of aerodynamic characteristics; compare the design dimension parameters of the above UAV with the empirical range of the dimension parameters to determine whether the initial value of the wing load iteration meets the requirements.

[0134] In an alternative embodiment, the design parameter determination module 522 is further configured to: in the case where the initial value of the wing area iteration does not meet the requirements, re-obtain the initial value of the wing area iteration; and / or in the case where the initial value of the wing load iteration does not meet the requirements, re-obtain the initial value of the wing load iteration.

[0135] In an alternative embodiment, the design parameters of the above UAV are the design parameters under single-cycle and constant-altitude flight, and the design parameter determination module 522 is further configured to: the above method further includes: based on the design parameters under single-cycle and constant-altitude flight, establish a multi-cycle and variable-altitude flight calculation model; optimize the multi-cycle and variable-altitude flight calculation model to obtain the final design parameters of the above UAV.

[0136] In an alternative embodiment, in the step of optimizing the multi-cycle and variable-altitude flight calculation model, the optimized variables are the solar cell module layout rate and the weight of the energy storage battery, and the result of the optimization minimizes the weight of the above UAV.

[0137] In an alternative embodiment, the above UAV is a solar UAV.

[0138] The embodiments of the present disclosure further provide a computer program product, including program code instructions, when the program product is executed by a computer, the program code instructions cause the computer to execute the method described above.

[0139] The embodiments of the present disclosure further provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the method described above.

[0140] The embodiments of the present disclosure further provide an electronic device, including: a processor, a memory in electronic communication with the processor; and instructions, the instructions are stored in the memory and executable by the processor to cause the electronic device to execute the method described above.

[0141] The embodiments of the present disclosure further provide a UAV, and the design parameters of the UAV are obtained based on the method described above.

[0142] For the specific details and technical effects of the computer program product, non-transitory computer-readable storage medium storing computer instructions, electronic device, and unmanned aerial vehicle (UAV) in the embodiments of the present disclosure, reference may be made to the description of the method for determining the design parameters of the UAV above, and details are not repeated here.

[0143] Based on the above, the present disclosure proposes the following technical solutions:

[0144] 1. A method for determining the design parameters of an unmanned aerial vehicle, comprising:

[0145] Obtaining wind field data of the location where the unmanned aerial vehicle flies;

[0146] Based on the wind field data, determining the design parameters of the unmanned aerial vehicle, where the design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, power characteristic parameters, and flight performance parameters.

[0147] 2. The method according to 1, wherein the obtaining of the wind field data of the location where the unmanned aerial vehicle flies comprises:

[0148] Obtaining the mission design objectives of the unmanned aerial vehicle, where the mission design objectives include mission latitude and mission date;

[0149] According to the mission latitude and the mission date, determining the wind field data of the location where the unmanned aerial vehicle flies.

[0150] 3. The method according to 1, wherein the determining of the design parameters of the unmanned aerial vehicle based on the wind field data comprises:

[0151] According to the wind field data, determining the minimum overnight height of the unmanned aerial vehicle;

[0152] Based on the minimum overnight height of the unmanned aerial vehicle, determining the design parameters of the unmanned aerial vehicle.

[0153] 4. The method according to 3, wherein the determining of the minimum overnight height of the unmanned aerial vehicle according to the wind field data comprises:

[0154] According to the intersection point of the reference wind speed - height curve and the flight speed - flight height curve, determining the flight height corresponding to the flight speed when the flight speed is equal to the reference wind speed, to obtain the minimum overnight height, where the reference wind speed is the maximum wind speed corresponding to a specific probability.

[0155] 5. The method according to 4, wherein the reference wind speed - height curve is obtained by the following method:

[0156] According to the wind field data, determining the reference wind speed corresponding to the mission design objectives, where the reference wind speed changes with height and forms a reference wind speed - height curve.

[0157] 6. The method according to claim 4, wherein the flight speed - flight altitude curve is obtained by the following method:

[0158] Based on the empirical values of wing loading and lift coefficient, determine the flight speed - flight altitude curve corresponding to the UAV.

[0159] 7. The method according to claim 1, wherein determining the design parameters of the UAV based on the minimum over - night altitude of the UAV includes:

[0160] Determine the initial iteration value of wing loading and the initial iteration value of wing area of the UAV.

[0161] Based on the minimum over - night altitude, the initial iteration value of wing loading and the initial iteration value of wing area, combined with the design task objectives and design input parameters of the UAV, determine the required endurance factor of the UAV from the perspective of energy conversion.

[0162] Based on the minimum over - night altitude, the initial iteration value of wing loading and the initial iteration value of wing area, combined with the design task objectives and design input parameters of the UAV, determine the designed endurance factor of the UAV from the perspective of aerodynamic characteristics.

[0163] Compare the required endurance factor and the designed endurance factor to determine whether the initial iteration value of wing area meets the requirements.

[0164] 8. The method according to claim 7, wherein determining the required endurance factor of the UAV from the perspective of energy conversion based on the minimum over - night altitude and the initial iteration value of wing area, combined with the design task objectives and design input parameters of the UAV, includes:

[0165] According to the minimum over - night altitude, the mission latitude, the mission date, the conversion efficiency of the solar cell module and the solar cell module layout ratio, determine the solar energy absorbed by the solar cell module per unit area in a single cycle according to the solar radiation power model.

[0166] According to the solar energy absorbed by the solar cell module per unit area in a single cycle and the charge - discharge efficiency of the energy storage battery, determine the available flight power per unit wing area according to the energy balance model.

[0167] According to the minimum over - night altitude, the available flight power per unit wing area, the initial iteration value of wing loading, the initial iteration value of wing area, the load power consumption and the propulsion system efficiency, determine the required endurance factor of the UAV according to the flight required power model.

[0168] 9. The method according to 7, wherein determining the design endurance factor of the UAV from the perspective of aerodynamic characteristics based on the minimum over-night height, the initial iteration value of wing loading, and the initial iteration value of wing area, in combination with the design mission objective and design input parameters of the UAV, includes:

[0169] Determine the weight per unit wing area of each subsystem according to the minimum over-night height, the initial iteration value of wing loading, and the initial iteration value of wing area, and determine the structural weight per unit wing area according to the weight model;

[0170] Determine the external dimension parameters of the UAV according to the structural weight per unit wing area and the UAV dimension model;

[0171] Determine the design endurance factor of the UAV based on the external dimension parameters of the UAV and the empirical formula of the UAV drag coefficient.

[0172] 10. The method according to 7, wherein determining the design parameters of the UAV based on the minimum over-night height of the UAV further includes:

[0173] Determine the maximum lift coefficient of the UAV according to the reference wind speed, the minimum over-night height, the initial iteration value of wing loading, and the initial iteration value of wing area;

[0174] Determine the design lift coefficient of the UAV from the perspective of aerodynamic characteristics based on the minimum over-night height, the initial iteration value of wing loading, and the initial iteration value of wing area, in combination with the design mission objective and design input parameters of the UAV;

[0175] Compare the maximum lift coefficient with the design lift coefficient to determine whether the initial iteration value of wing area meets the requirements.

[0176] 11. The method according to 10, wherein determining the design parameters of the UAV based on the minimum over-night height of the UAV further includes:

[0177] Determine the design dimension parameters of the UAV from the perspective of aerodynamic characteristics based on the minimum over-night height, the initial iteration value of wing loading, and the initial iteration value of wing area, in combination with the design mission objective and design input parameters of the UAV;

[0178] Compare the design dimension parameters of the UAV with the empirical range of dimension parameters to determine whether the initial iteration value of wing loading meets the requirements.

[0179] 12. The method according to 11, wherein the method further includes:

[0180] In the case where the initial value of the wing area iteration does not meet the requirements, re-obtain the initial value of the wing area iteration; and / or

[0181] In the case where the initial value of the wing load iteration does not meet the requirements, re-obtain the initial value of the wing load iteration.

[0182] 13. The method according to 1, wherein the design parameters of the UAV are the design parameters under single-cycle and constant-altitude flight; and

[0183] The method further includes:

[0184] Based on the design parameters under single-cycle and constant-altitude flight, establish a multi-cycle and variable-altitude flight calculation model;

[0185] Optimize the multi-cycle and variable-altitude flight calculation model to obtain the final design parameters of the UAV.

[0186] 14. The method according to 13, wherein in the step of optimizing the multi-cycle and variable-altitude flight calculation model, the optimized variables are the layout ratio of the solar cell modules and the weight of the energy storage battery, and the optimization result minimizes the weight of the UAV.

[0187] 15. The method according to any one of 1-14, wherein the UAV is a solar UAV.

[0188] 16. A device for determining the design parameters of a UAV, comprising:

[0189] A wind field data acquisition module for acquiring the wind field data at the location where the UAV flies;

[0190] A design parameter determination module for determining the design parameters of the UAV based on the wind field data, where the design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, power characteristic parameters, and flight performance parameters.

[0191] 17. The device according to 16, wherein the wind field data acquisition module includes a mission design target acquisition module and a wind field data determination module, the mission design target acquisition module is used to acquire the mission design target of the UAV, and the mission design target includes mission latitude and mission date; the wind field data determination module is used to determine the wind field data corresponding to the mission design target according to the mission latitude and the mission date.

[0192] 18. The device according to claim 16, wherein the design parameter determination module comprises a minimum overnight altitude determination module and a design parameter determination module. The minimum overnight altitude determination module is configured to determine the minimum overnight altitude of the unmanned aerial vehicle according to the wind field data, and the design parameter determination module is configured to determine the design parameters of the unmanned aerial vehicle based on the minimum overnight altitude of the unmanned aerial vehicle.

[0193] 19. The device according to claim 18, wherein the minimum overnight altitude determination module is further configured to: determine the flight altitude corresponding to the flight speed when the flight speed is equal to the reference wind speed according to the intersection point of the reference wind speed - altitude curve and the flight speed - flight altitude curve, so as to obtain the minimum overnight altitude, wherein the reference wind speed is the maximum wind speed corresponding to a specific probability.

[0194] 20. The device according to claim 18, wherein the design parameter determination module is further configured to: determine the initial iteration value of the wing loading and the initial iteration value of the wing area of the unmanned aerial vehicle; based on the minimum overnight altitude, the initial iteration value of the wing loading and the initial iteration value of the wing area, in combination with the design task objective and the design input parameters of the unmanned aerial vehicle, determine the required endurance factor of the unmanned aerial vehicle from the perspective of energy conversion; based on the minimum overnight altitude, the initial iteration value of the wing loading and the initial iteration value of the wing area, in combination with the design task objective and the design input parameters of the unmanned aerial vehicle, determine the design endurance factor of the unmanned aerial vehicle from the perspective of aerodynamic characteristics; compare the required endurance factor with the design endurance factor to determine whether the initial iteration value of the wing area meets the requirements.

[0195] 21. A computer program product comprising program code instructions, which when executed by a computer, cause the computer to execute the method according to any one of claims 1 - 15.

[0196] 22. A non - transitory computer - readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the method according to any one of claims 1 - 15.

[0197] 23. An electronic device, comprising:

[0198] a processor,

[0199] a memory in electronic communication with the processor; and

[0200] instructions stored in the memory and executable by the processor to cause the electronic device to execute the method according to any one of claims 1 - 15.

[0201] 24. A drone, wherein the design parameters of the drone are obtained based on any one of the methods described in Items 1 - 15.

[0202] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes may be made therein without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for determining the design parameters of an unmanned aerial vehicle, comprising: Obtaining the wind field data at the location where the unmanned aerial vehicle flies; Based on the wind field data, determining the design parameters of the unmanned aerial vehicle, where the design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, power characteristic parameters, and flight performance parameters; The determining the design parameters of the unmanned aerial vehicle based on the wind field data includes: according to the wind field data, determining the minimum over-night height of the unmanned aerial vehicle; based on the minimum over-night height of the unmanned aerial vehicle, determining the design parameters of the unmanned aerial vehicle; the over-night height is the maximum height of the unmanned aerial vehicle during night cruise; The determining the minimum over-night height of the unmanned aerial vehicle according to the wind field data includes: according to the intersection point of the reference wind speed-height curve and the flight speed-flight height curve, determining the flight height corresponding to the flight speed when the flight speed is equal to the reference wind speed, to obtain the minimum over-night height, where the reference wind speed is the maximum wind speed corresponding to a specific probability; The determining the design parameters of the unmanned aerial vehicle based on the minimum over-night height of the unmanned aerial vehicle includes: determining the initial iteration value of the wing loading and the initial iteration value of the wing area of the unmanned aerial vehicle; based on the minimum over-night height, the initial iteration value of the wing loading, and the initial iteration value of the wing area, combined with the design task objective and design input parameters of the unmanned aerial vehicle, determining the required endurance factor of the unmanned aerial vehicle from the perspective of energy conversion; based on the minimum over-night height, the initial iteration value of the wing loading, and the initial iteration value of the wing area, combined with the design task objective and design input parameters of the unmanned aerial vehicle, determining the design endurance factor of the unmanned aerial vehicle from the perspective of aerodynamic characteristics; comparing the required endurance factor and the design endurance factor to determine whether the initial iteration value of the wing area meets the requirements.

2. The method according to claim 1, wherein The obtaining the wind field data at the location where the unmanned aerial vehicle flies includes: Obtaining the mission design objective of the unmanned aerial vehicle, where the mission design objective includes mission latitude and mission date; According to the mission latitude and the mission date, determining the wind field data at the location where the unmanned aerial vehicle flies.

3. The method according to claim 1, wherein The reference wind speed-height curve is obtained by the following method: According to the wind field data, determining the reference wind speed corresponding to the mission design objective, where the reference wind speed changes with height and forms a reference wind speed-height curve.

4. The method according to claim 1, wherein, The flight speed-flight height curve is obtained by the following method: Based on the empirical value of the wing loading and the empirical value of the lift coefficient, determining the flight speed-flight height curve corresponding to the unmanned aerial vehicle.

5. The method according to claim 2, wherein, The determining the required endurance factor of the unmanned aerial vehicle from the perspective of energy conversion based on the minimum over-night height and the initial iteration value of the wing area, combined with the design task objective and design input parameters of the unmanned aerial vehicle, includes: According to the minimum over-night height, the mission latitude, the mission date, the conversion efficiency of the solar cell module, and the solar cell module layout ratio, determining the solar energy absorbed by the solar cell module per unit area within a single cycle period according to the solar radiation power model; Determine the available flight power per unit wing area according to the solar energy absorbed by the solar cell module per unit area within the single-cycle period and the charge-discharge efficiency of the energy storage battery, in accordance with the energy balance model. Determine the required endurance factor of the UAV according to the minimum over-night height, the available flight power per unit wing area, the initial value of wing loading iteration, the initial value of wing area iteration, the load power consumption, and the propulsion system efficiency, in accordance with the required flight power model.

6. The method according to claim 1, wherein Based on the minimum over-night height, the initial value of wing loading iteration, and the initial value of wing area iteration, and in combination with the design task objective and design input parameters of the UAV, determine the design endurance factor of the UAV from the perspective of aerodynamic characteristics, including: Determine the weight per unit wing area of each subsystem according to the minimum over-night height, the initial value of wing loading iteration, and the initial value of wing area iteration, and determine the structural weight per unit wing area in accordance with the weight model. Determine the external dimension parameters of the UAV according to the structural weight per unit wing area in accordance with the UAV dimension model. Determine the design endurance factor of the UAV based on the external dimension parameters of the UAV and the empirical formula of the UAV drag coefficient.

7. The method according to claim 1, wherein Based on the minimum over-night height of the UAV, determining the design parameters of the UAV further includes: Determine the maximum lift coefficient of the UAV according to the reference wind speed, the minimum over-night height, the initial value of wing loading iteration, and the initial value of wing area iteration. Based on the minimum over-night height, the initial value of wing loading iteration, and the initial value of wing area iteration, and in combination with the design task objective and design input parameters of the UAV, determine the design lift coefficient of the UAV from the perspective of aerodynamic characteristics. Compare the maximum lift coefficient with the design lift coefficient to determine whether the initial value of wing area iteration meets the requirements.

8. The method according to claim 7, wherein, Based on the minimum over-night height of the UAV, determining the design parameters of the UAV further includes: Based on the minimum over-night height, the initial value of wing loading iteration, and the initial value of wing area iteration, and in combination with the design task objective and design input parameters of the UAV, determine the design dimension parameters of the UAV from the perspective of aerodynamic characteristics. Compare the design dimension parameters of the UAV with the empirical range of dimension parameters to determine whether the initial value of wing loading iteration meets the requirements.

9. The method according to claim 8, wherein, The method further includes: In the case where the initial value of wing area iteration does not meet the requirements, re-obtain the initial value of wing area iteration; and / or In the case where the initial value of wing loading iteration does not meet the requirements, re-obtain the initial value of wing loading iteration.

10. The method according to claim 1, wherein, The design parameters of the UAV are the design parameters under single-cycle and constant-altitude flight; and The method further includes: Based on the design parameters under single-cycle and constant-altitude flight, establish a multi-cycle and variable-altitude flight calculation model; Optimize the multi-cycle and variable-altitude flight calculation model to obtain the final design parameters of the UAV.

11. The method according to claim 10, wherein In the step of optimizing the multi-cycle, variable altitude flight calculation model, the variables to be optimized are the layout rate of the solar cell modules and the weight of the energy storage battery, and the optimization result minimizes the weight of the UAV.

12. The method according to any one of claims 1-11, wherein The UAV is a solar UAV.

13. A device for determining design parameters of a UAV, comprising: A wind field data acquisition module for acquiring wind field data at the location where the UAV flies; A design parameter determination module for determining the design parameters of the UAV based on the wind field data, where the design parameters include at least one of weight characteristic parameters, geometric shape parameters, aerodynamic characteristic parameters, power characteristic parameters, and flight performance parameters; The design parameter determination module includes a minimum overnight altitude determination module and a design parameter determination module. The minimum overnight altitude determination module is used to determine the minimum overnight altitude of the UAV according to the wind field data, where the overnight altitude is the maximum altitude for the UAV to cruise at night, and the design parameter determination module is used to determine the design parameters of the UAV based on the minimum overnight altitude of the UAV; The minimum overnight altitude determination module is further used to: determine the flight altitude corresponding to the flight speed when the flight speed is equal to the reference wind speed according to the intersection point of the reference wind speed - altitude curve and the flight speed - flight altitude curve, so as to obtain the minimum overnight altitude, where the reference wind speed is the maximum wind speed corresponding to a specific probability; The design parameter determination module is further used to: determine the initial iteration value of the wing loading and the initial iteration value of the wing area of the UAV; based on the minimum overnight altitude, the initial iteration value of the wing loading, and the initial iteration value of the wing area, combined with the design task objective and design input parameters of the UAV, determine the required endurance factor of the UAV from the perspective of energy conversion; based on the minimum overnight altitude, the initial iteration value of the wing loading, and the initial iteration value of the wing area, combined with the design task objective and design input parameters of the UAV, determine the design endurance factor of the UAV from the perspective of aerodynamic characteristics; Compare the required endurance factor and the design endurance factor to determine whether the initial iteration value of the wing area meets the requirements.

14. The apparatus according to claim 13, wherein, The wind field data acquisition module includes a task design objective acquisition module and a wind field data determination module. The task design objective acquisition module is used to acquire the task design objective of the UAV, where the task design objective includes the task latitude and the task date; the wind field data determination module is used to determine the wind field data corresponding to the task design objective according to the task latitude and the task date.

15. A computer program product, comprising program code instructions, which when executed by a computer, cause the computer to execute the method according to any one of claims 1 - 12.

16. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1 - 12.

17. An electronic device, comprising: A processor, A memory in electronic communication with the processor; And An instruction, which is stored in the memory and executable by the processor to cause the electronic device to execute the method according to any one of claims 1-12.

18. A drone, the design parameters of which are obtained based on the method according to any one of claims 1-12.

Images