Design method of high-speed multi-rotor blades

Abstract

The present invention discloses a method for designing high-speed multi-rotor blades. In the method, the approximate range of blade sizes is first limited by known basic data and expected data to obtain the force balance equation of the drone. Then, a sufficient number of specific blade sizes that meet the limited range are given. By comparing expected performance indicators, data is screened from the given blade sizes, adjusted in a random crossover manner, and screened again. This is repeated multiple times until the expected performance indicators can be obtained. If the expected performance indicators cannot be obtained, the initial amount of specific blade size data is increased, the output volume of each screening is reduced, and the screening process is executed again.

Description

Technical Field

[0001] The present invention relates to a design method for a UAV blade, and in particular to a design method for a high-speed multi-rotor blade. Background Art

[0002] Multi-rotor drones are now widely used in military and civilian fields due to their maneuverability and flexibility. As multi-rotor drones are used in more and more scenarios, their flight speed has become a major limitation. Currently, most multi-rotor blades on the market are designed for hovering and do not take into account the overall aerodynamic characteristics. As a result, the efficiency of current multi-rotor drones in forward flight is low.

[0003] In response to the above problems, the present invention has conducted in-depth research on the design method of high-speed multi-rotor blades for drones under high-speed forward flight conditions, in the hope of proposing a new design method for high-speed multi-rotor blades that can solve the above problems. Summary of the Invention

[0004] In order to overcome the above problems, the inventors conducted intensive research and designed a method for designing high-speed multi-rotor blades. In this method, the approximate range of blade sizes is first limited by known basic data and expected data to obtain the force balance equation of the drone, and then a sufficient number of specific blade sizes that meet the limited range are given. By comparing the expected performance indicators, data is screened from the given blade sizes, adjusted in a random crossover manner, and screened again. This is repeated multiple times until the expected performance indicators can be obtained. If the expected performance indicators cannot be obtained, the initial amount of specific blade size data is increased, the output of each screening is reduced, and the screening process is performed again, thereby completing the present invention.

[0005] Specifically, the present invention aims to provide a method for designing high-speed multi-rotor blades, the method comprising the following steps:

[0006] Step 1: Determine a preliminary blade size range based on expected parameters; the expected parameters include takeoff weight, fuselage size, flight radius, flight time, and maximum output power; and the blade size includes blade diameter, chord length, and torsion angle.

[0007] Step 2: establishing an aerodynamic model of the blade according to the preliminary blade size range;

[0008] Step 3: Establishing a force balance equation for the UAV based on the aerodynamic model of the blades to obtain the relationship between blade size and the performance indicators of the UAV, including flight time, maximum output power, maximum flight speed, overload, and takeoff weight;

[0009] Step 4: Gradually adjust the value of the blade size through optimization iteration until the value of the blade size can obtain the desired performance index.

[0010] Among them, in Step 1, the preliminary blade size range is obtained through the following formula (I):

[0011] R = (1.04r p ~1.21r p ) / sin(180° / n) (I)

[0012] Where R is the radius of the drone fuselage, r p is the radius of the propeller, and n is the number of propellers.

[0013] Among them, in Step 2, the aerodynamic model of the blade includes the following formula (IV);

[0014]

[0015] Where T p represents the tensile force on the blade; H p represents the drag force on the blade; Q P represents the torque on the blade; represents the pitching moment on the blade;

[0016] t1, t2, t3, t4 all represent the tensile force model parameters,

[0017] Ω represents the rotational speed; V represents the flight speed, rotational speed, and flight speed;

[0018] α p represents the angle between the oncoming flow and the blade surface;

[0019] h1, h2 both represent the drag force model parameters;

[0020] q1, q2, q3, qA all represent the torque model parameters; ​​​​​​​​​​​​​​​​​​​​​

[0027] J represents the moment of inertia;

[0028] It represents the pitch moment of the fuselage, T1 represents the pull of the front propeller on the fuselage, T2 represents the pull of the rear propeller on the fuselage, l represents the distance from the center of mass of the blade to the center of mass of the drone, H1 represents the force parallel to the blade generated by the front propeller, H2 represents the force parallel to the blade generated by the rear propeller, d1 represents the diameter of the front propeller, and d2 represents the diameter of the rear propeller.

[0029] Ω1 and Ω2 represent the rotation speed of the front and rear propellers, respectively, and their values ​​are 4500 rpm;

[0030] η m (I) represents the motor conversion efficiency, which is 80;

[0031] Q p (α, V, Ω1) represents the torque of the front propeller, Q p (α, V, Ω2) represents the torque of the rear propeller;

[0032] η m (I) represents the motor conversion efficiency;

[0033] V represents the speed in the x-axis direction, and U represents the speed in the y-axis direction. represents the blade azimuth, P represents the power;

[0034] When the drone is in a balanced state,

[0035] Wherein, the step 4 includes the following sub-steps:

[0036] Sub-step 1: randomly providing a predetermined number of specific blade sizes; each of the specific blade sizes includes a specific size of a blade diameter, a specific size of a blade chord length, and a specific size of a blade torsion angle; and each of the specific blade sizes falls within the preliminary blade size range;

[0037] Sub-step 2: for each specific set of blade dimensions, a corresponding set of performance index values ​​is obtained through the force balance equation, thereby obtaining a predetermined number of performance index data;

[0038] Sub-step 3, selecting some data with better performance from a predetermined number of performance index data, finding the specific blade size corresponding to each set of performance index values, and recording them as the first-level screening size data;

[0039] Sub-step 4: randomly cross the corresponding relationships of each sub-item in the first-level screening dimension data to obtain first-level cross dimension data;

[0040] Sub-step 5, replacing the specific blade size randomly given in sub-step 1 with the first-level cross-size data, repeating sub-steps 1, 2, and 3 to obtain second-level screening size data, and then repeating sub-step 4 to obtain second-level cross-size data;

[0041] Sub-step 6: Repeat sub-step 5 multiple times until the performance index obtained in sub-step 2 meets the expected performance index, and record the blade size value corresponding to the expected performance index.

[0042] Among them, in sub-step 3, the predetermined number of performance indicator data obtained in sub-step 2 are analyzed one by one, and the specific items contained in each group of performance indicator data, namely, the flight time value, the maximum output power value, the maximum flight speed value, the overload value and the take-off weight value are analyzed. When one value in the item is greater than the corresponding value in the expected performance indicator, the data is first-level optional data; when two values ​​in the item are greater than the corresponding values ​​in the expected performance indicator, the data is second-level optional data; when three values ​​in the item are greater than the corresponding values ​​in the expected performance indicator, the data is third-level optional data; when four values ​​in the item are greater than the corresponding values ​​in the expected performance indicator, the data is fourth-level optional data; when five values ​​in the item are all greater than the corresponding values ​​in the expected performance indicator, the data is fifth-level optional data.

[0043] The number of the data with better performance is the screening number, and there is a proportional relationship between the screening number and the predetermined number in sub-step 2. Preferably, the screening number is 60-80% of the predetermined number.

[0044] The beneficial effects of the present invention include:

[0045] (1) The method for designing high-speed multi-rotor blades provided by the present invention can quickly and accurately design rotor blades that can meet the specific performance requirements of a specific drone in a specific application scenario;

[0046] (2) The method for designing high-speed multi-rotor blades provided by the present invention is a highly versatile method that can quickly and accurately provide design parameters for drones of different sizes, different take-off weights, and different working purposes. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 An overall logic diagram of a design method for high-speed multi-rotor blades according to a preferred embodiment of the present invention is shown. DETAILED DESCRIPTION

[0048] The present invention will be described in further detail below with reference to the accompanying drawings and examples, through which the features and advantages of the present invention will become more clearly understood.

[0049] As used herein, the term "exemplary" means "serving as an example, embodiment or illustration". Any embodiment described as "exemplary" herein is not necessarily to be construed as superior or better than other embodiments. Although various aspects of the embodiments are shown in the drawings, the drawings do not have to be drawn to scale unless specifically stated.

[0050] A design method for a high-speed multi-rotor blade according to the present invention is characterized in that the method comprises the following steps:

[0051] Step 1, determining a preliminary blade size range according to expected parameters; the expected parameters include take-off weight, fuselage radius, flight radius, flight time and maximum output power, and the blade size includes the diameter, chord length and twist angle of the blade;

[0052] Step 2, establishing an aerodynamic model of the blade according to the preliminary blade size range;

[0053] Step 3, establishing a force balance equation of the unmanned aerial vehicle based on the aerodynamic model of the blade, obtaining the functional relationship between the blade size and the performance indexes of the unmanned aerial vehicle, and the performance indexes include flight time, maximum output power, maximum flight speed, overload and take-off weight;

[0054] Step 4, gradually adjusting the value of the blade size through optimization iteration until the value of the blade size can obtain the desired performance indexes. <0000?

[0055] In a preferred embodiment, in Step 1, the preliminary blade size range is obtained according to the aerodynamic characteristics of the blade determined by methods such as empirical formulas and CFD simulations. For example, the relationship between the fuselage radius R of the unmanned aerial vehicle and the propeller radius, i.e., the diameter r of the blade, is as shown in the following formula (I), where n represents the number of propellers. [[ID=?]] p is as follows, where n represents the number of propellers

[0056] R = (1.04r p ~1.21r p ) / sin(180° / n) (I)

[0057] The chord length c p is set using an empirical formula related to the propeller radius. For example, the chord length at two-thirds of the propeller radius is taken as the propeller chord length, as shown in the following formula:

[0058]

[0059] The twist angle is generally selected within a predetermined range, such as set as

[0060] The expected parameters are the design targets for high-speed multi-rotor blades. In order to obtain a preliminary range of blade sizes, taking a small UAV as an example, a set of specific targets can be set as follows: the required expected parameters include a take-off weight of 5.15 kg, a fuselage diameter of 550 mm, a flight radius of 3 km, a flight time of 30 minutes, and a maximum output power of 2 kW.

[0061] Preferably, during the actual design process, the actual takeoff weight needs to be calculated based on the specific design arrangement. The takeoff weight is obtained by the following formula (2):

[0062]

[0063] Among them, GTOW represents the takeoff weight; the values ​​of other parameters in the formula are related to other parameters of the UAV to be designed. Taking the small UAV described above as an example, the corresponding parameter values ​​are as follows:

[0064] W pld Indicates the load mass, its value is 1.2kg;

[0065] W dev Indicates the mass of avionics equipment, and its value is 0.8kg;

[0066] ξ m The motor structure coefficient is the ratio of the motor weight to the takeoff weight, and its value is 0.113;

[0067] ξ b The battery structure factor is the ratio of the battery weight to the takeoff weight, and its value is 0.379;

[0068] ξ s It represents the airframe structural coefficient, which is the ratio of the structural weight to the takeoff weight, and its value is 0.120;

[0069] The b Obtained by the following formula (3):

[0070]

[0071] time represents the flight time; EFF represents the force efficiency when the drone is hovering, with a value of 8 to 10; g represents the acceleration due to gravity; BCD represents the battery capacity density, with a value of 180 to 230Wh / kg.

[0072] Preferably, the fuselage size includes the fuselage radius and the aerodynamic model of the fuselage. Specifically, the aerodynamic model of the fuselage is shown in the following formula:

[0073]

[0074] Among them, L f 、Df 、 They represent the lift, drag and pitching moment acting on the fuselage respectively;

[0075] c y (α), c x (α), c m (α) represents the lift coefficient, drag coefficient, and pitching moment coefficient, respectively;

[0076] ρ represents the air density, which can be taken as 1.293 kg / m 3 ; V represents the flight speed, which can be 20m / s; S represents the cross-sectional area of ​​the fuselage, which can be 50cm 2 .

[0077] In a preferred embodiment, in step 2, the aerodynamic model of the blade includes the following formula (4):

[0078]

[0079] Among them, T p Indicates the tension on the blade; H p Indicates the resistance on the blade; Q P Indicates the torque on the blade; represents the pitching moment on the blade; the specific values ​​of the tension model parameters, drag model parameters, torque model parameters, and pitching moment model parameters in formula (4) all need to be based on the blade size and are related to the blade size. For specific correlations, please refer to "Forward Flight Modal Characteristics of Quadrotor UAV" in "Acta Armamentarii", by Ye Jianchuan, Wang Jiang, Liang Yi, Song Tao, Wu Zeliang, and Xu Chao.

[0080] In this application, a small UAV is taken as an example to illustrate the specific values ​​of the above parameters. t1, t2, t3, and t4 all represent tension model parameters, and their values ​​are t1 = 1.028 × 10 -6 , t2=8.401×10 -5 , t3=-1.945×10 -4 , t4=-0.0193;

[0081] Ω represents the rotation speed, which ranges from 3000 to 6500 rpm; V represents the flight speed, which ranges from 0 to 30 m / s;

[0082] α p Indicates the angle between the incoming flow and the blade surface, and its value ranges from 0 to 30°;

[0083] h1 and h2 both represent resistance model parameters, and their values ​​are h1=8.574×10 -6 , h2=-0.0024;

[0084] q1, q2, q3, and q4 all represent torque model parameters, and their values ​​are q1 = 2.19 × 10 -8 ,q2=1.79×10 -5 ,q3=9.97×10 -7 ,q4=-4.29×10 -12 ;

[0085] m1, m2, and m3 all represent pitch moment model parameters, and their values ​​are m1 = 5.88 × 10 -4 , m2=7.39×10 -6 , m3=4.964×10 -7 .

[0086] In a preferred embodiment, in step 3, when the UAV is a quad-rotor UAV, its force balance equation includes the following formula (5):

[0087]

[0088] In this application, a small drone is taken as an example to illustrate the specific values ​​of the above parameters. m represents the mass of the drone, and its value is 5.15 kg;

[0089] α and θ represent the angle of attack and pitch angle, respectively, and their values ​​range from 0 to 30°. The specific values ​​vary with the state.

[0090] T p1 Indicates the tension on the front blade, T p2 The sum of the two is the pulling force T on the drone. p ;

[0091] H p1 Indicates the resistance on the front blade, H p2 The sum of the two is the resistance on the drone;

[0092] represents the pitching moment on the front blade, It represents the pitch moment on the rear blade. The sum of the two is the pitch moment on the drone.

[0093] D F and L Frepresents fuselage drag and fuselage lift, respectively. Their values ​​are obtained through wind tunnel testing and are assumed to be 5 N in this application. A wind tunnel is a pipe-like test device that artificially generates and controls airflow to simulate the flow of gas around an aircraft or object, measure the effects of airflow on the object, and observe physical phenomena. The wind tunnel used in this invention has a maximum wind speed of 80 m / s, a minimum turbulence of 0.08%, and a working section cross-sectional dimensions of 1.2 m x 1.2 m.

[0094] J represents the moment of inertia, and its value is obtained through the three-wire pendulum experiment, preferably 0.48 kg·m 2 ; The three-wire pendulum refers to a method for measuring the moment of inertia of an object through torsional motion.

[0095] It represents the pitch moment of the fuselage, and its value is obtained through wind tunnel test, preferably 1N·cm; T1 represents the sum of the pulling forces of the two front propellers on the fuselage, and its value is 20N; T2 represents the sum of the pulling forces of the two rear propellers on the fuselage, and its value is 20N; l represents the distance from the center of mass of the blade to the center of mass of the UAV, and its value is obtained through measurement, which is 275mm; H1 represents the sum of the resistance of the two front propellers on the fuselage, and its value is 15N; H2 represents the sum of the resistance of the two rear propellers on the fuselage, and its value is 15N; d1 represents the diameter of the front propeller blade, and its value is obtained through measurement, preferably 210mm; d2 represents the diameter of the rear propeller blade, and its value is obtained through measurement, and its value is 210mm.

[0096] Q p (α, V, Ω1) represents the torque of the front propeller, Q p (α, V, Ω2) represents the torque of the rear propeller;

[0097] Ω1 and Ω2 represent the rotation speeds of the front and rear propellers, respectively. Their values ​​are obtained through measurement and are both 4500 rpm.

[0098] η m (I) represents the motor conversion efficiency, which is 80%;

[0099] V represents the speed in the X-axis direction, and its value is obtained through wind tunnel tests and is 0 to 30 m / s; U represents the speed in the Y-axis direction, and its value is 0 m / s in forward flight conditions; Indicates the blade azimuth angle, which ranges from 0 to 360°; P indicates power, which ranges from 500 to 2000W;

[0100] When the drone is in a balanced state, Solving the above equations reveals how the drone's pitch angle changes with speed, how its power changes with speed, and how the front and rear propellers change with speed. This allows us to determine parameters such as the drone's maximum flight speed, power consumption during hovering, and power consumption during cruising.

[0101] In a preferred embodiment, step 4 includes the following sub-steps:

[0102] Sub-step 1: randomly providing a predetermined number of specific blade sizes; each of the specific blade sizes includes a specific size of a blade diameter, a specific size of a blade chord length, and a specific size of a blade torsion angle; and each of the specific blade sizes falls within the preliminary blade size range;

[0103] Sub-step 2: for each specific set of blade dimensions, a corresponding set of performance index values ​​is obtained through the force balance equation, thereby obtaining a predetermined number of performance index data;

[0104] Sub-step 3, selecting some data with better performance from a predetermined number of performance index data, finding the specific blade size corresponding to each set of performance index values, and recording them as the first-level screening size data;

[0105] Sub-step 4: randomly cross the corresponding relationships of each sub-item in the first-level screening dimension data to obtain first-level cross dimension data;

[0106] Sub-step 5, replacing the specific blade size randomly given in sub-step 1 with the first-level cross-size data, repeating sub-steps 1, 2, and 3 to obtain second-level screening size data, and then repeating sub-step 4 to obtain second-level cross-size data;

[0107] Sub-step 6: Repeat sub-step 5 multiple times until the performance index obtained in sub-step 2 meets the expected performance index, and record the blade size value corresponding to the expected performance index.

[0108] In a preferred embodiment, in sub-step 1, the specific value of the predetermined number is selected according to the difficulty of the performance indicator and the requirement for calculation speed, and the specific value of the number fluctuates greatly, such as 100 to 300, etc.

[0109] In a preferred embodiment, if 200 groups of specific blade sizes are randomly given in sub-step 1, then in sub-step 2, 200 groups of performance index values ​​are obtained accordingly, and each group of specific blade sizes corresponds to a group of performance index values, and each group of performance index values ​​includes a specific flight time value, a specific maximum output power value, a specific maximum flight speed value, a specific overload value and a specific take-off weight value.

[0110] Preferably, the desired performance indicators include specific parameter critical values ​​that the designed drone is expected to achieve. In actual operation, the specific critical values ​​will be used as the lower limit. For example, if the expected flight time is 1800s, data that makes the flight time greater than 1800s will be selected during design.

[0111] In a preferred embodiment, in sub-step 3, a predetermined number of performance index data obtained in sub-step 2 are analyzed one by one, and the specific items contained in each set of performance index data, namely, the flight time value, the maximum output power value, the maximum flight speed value, the overload value and the take-off weight value, are analyzed. If one value of these items is greater than the corresponding value in the expected performance index, the data is considered to be first-level optional data; if two values ​​of these items are greater than the corresponding values ​​in the expected performance index, the data is considered to be second-level optional data; if three values ​​of these items are greater than the corresponding values ​​in the expected performance index, the data is considered to be third-level optional data; if four values ​​of these items are greater than the corresponding values ​​in the expected performance index, the data is considered to be fourth-level optional data; if five values ​​of these items are greater than the corresponding values ​​in the expected performance index, the data is considered to be fifth-level optional data, and the drone can be designed according to the blade size in the data.

[0112] In sub-step 3, the number of data with better performance is called the screening number. There is a proportional relationship between the screening number and the predetermined number in sub-step 2. The specific proportional relationship needs to be selected based on the difficulty of the performance indicators and the requirements for calculation speed; preferably, the screening number is 60-80% of the predetermined number, preferably 70%.

[0113] In sub-step 3, when selecting some data with better performance from a predetermined number of performance index data, first randomly select from the four-level optional data. If the number of four-level optional data is insufficient to meet the screening number requirements, then select all the four-level optional data, and then randomly select from the three-level optional data to supplement. If the number of three-level optional data is insufficient to meet the screening number requirements, then select all the three-level optional data, and then randomly select from the two-level optional data to supplement. If the number of two-level optional data is insufficient to meet the screening number requirements, then select all the two-level optional data, and then randomly select from the first-level optional data to supplement. If the number of first-level optional data is insufficient to meet the screening number requirements, then select all the first-level optional data. At this time, you can randomly select from the remaining data to make the screening number reach 60-80% of the predetermined number.

[0114] Preferably, in sub-step 3, the number of specific blade size data obtained is consistent with the screening number, that is, each set of performance index data corresponds to a set of specific blade size data.

[0115] In a preferred embodiment, in sub-step 4, the primary screening size data includes multiple groups of specific blade sizes, each group of specific blade sizes includes three sub-items, namely, the blade diameter size, the blade chord length size, and the blade torsion angle size;

[0116] Preferably, randomly crossing the correspondence between the sub-items means exchanging any sub-item in a specific blade size with the corresponding sub-item in any other specific blade size. During the crossing process, it is ensured that one or two sub-items in each specific blade size cross with the sub-items in other specific blade sizes.

[0117] For example, among the many specific blade sizes included in the first-level screening size data, one group of specific blade sizes is: blade diameter 210mm, blade chord length 24mm, blade torsion angle 17.6 degrees; another group of specific blade sizes is: blade diameter 212mm, blade chord length 23mm, blade torsion angle 17.1 degrees; crossing the correspondence between the sub-items in the above two groups of specific blade sizes, one group of specific blade sizes is obtained: blade diameter 212mm, blade chord length 24mm, blade torsion angle 17.6 degrees; another group of specific blade sizes is: blade diameter 210mm, blade chord length 23mm, blade torsion angle 17.1.

[0118] All the specific blade size data after crossing constitute the first-level crossing size data.

[0119] Preferably, each time a cross operation is performed, a cross task is recorded. During the execution of sub-step 4, the ratio of the total number of cross tasks to the total amount of specific blade size data in the first-level screening size data is recorded as the cross rate. When executing sub-step 4, the cross rate is controlled at 70-90%, preferably 80%.

[0120] In a preferred embodiment, each time sub-step 5 is performed, the total amount of data will be reduced accordingly, and the specific amount of reduction is determined by the proportional relationship between the screening amount and the predetermined amount.

[0121] The data obtained by executing sub-step 5 for the first time is the secondary cross-size data. When executing sub-step 5 for the second time, the secondary cross-size data is used to replace the specific blade size randomly given in sub-step 1, and then sub-steps 1, 2, and 3 are repeated to obtain the tertiary screening size data, and then sub-step 4 is repeated to obtain the tertiary cross-size data.

[0122] In a preferred embodiment, in sub-step 6, when the performance metrics obtained in sub-step 2 meet the expected performance metrics, it means that the five-level optional data appears. At this time, the iteration is completed, and the drone blades can be designed according to the blade size corresponding to the five-level optional data.

[0123] When continuously executing sub-step 6, if the number of specific blade size data is less than 5 and the five-level optional data cannot be obtained, then return to sub-step 1, increase the predetermined number of specific values, and restart the calculation from sub-step 1.

[0124] When the predetermined number reaches the preset maximum value and the five-level optional data still cannot be obtained, feedback that the performance metrics are unreasonable and adjust the performance metrics.

[0125] Embodiment

[0126] Design a high-speed multi-rotor blade, and the expected parameters involved are as follows: <(

[0127] Takeoff weight: 5.15 kg;

[0128] Fuselage size: 550 mm;

[0129] Flight radius: 3 km;

[0130] Flight time: 30 min;

[0131] Maximum output power: 2 kW.

[0132] The expected performance metrics are:

[0133] Flight time: 30 min;

[0134] Maximum output power: 2 kW;

[0135] Maximum flight speed: 33.05 m / s;

[0136] Overload: 3 g;

[0137] Takeoff weight: 5.15 kg;

[0138] According to the expected parameters, determine the preliminary blade size range through the following formula (1):

[0139] R = (1.04r p ~1.21r p ) / sin(180° / n) (1)

[0140] c p = c p (2 / 3r p )

[0141]

[0142] The resulting preliminary blade size range is:

[0143] The diameter is in the range of 160~196mm.

[0144] The string length is in the range of 20 to 45 mm.

[0145] The torsion angle is in the range of 5 to 25 degrees.

[0146] The aerodynamic model of the blade is established as the following formula (4):

[0147]

[0148] Among them, the values ​​of t1, t2, t3, and t4 are 1.028×10 -6 , 8.401×10 -5 , -1.945×10 -4 , -0.0193;

[0149] The values ​​of h1 and h2 are 8.574×10 -6 , -0.0024;

[0150] The values ​​of q1, q2, q3, and q4 are 2.19×10 -8 , 1.79×10 -5 , 9.97×10 -7 , -4.29×10 -12 ;

[0151] The values ​​of m1, m2, and m3 are 5.88×10 -4 , 7.39×10 -6 , 4.964×10 -7 .

[0152] The force balance equation of the UAV includes the following formula (5):

[0153]

[0154] Among them, the specific value of l is 275mm.

[0155] Sub-step 1: randomly generate 1000 sets of specific blade sizes within the preliminary blade size range;

[0156] Sub-step 2, obtaining 1000 sets of corresponding performance index values ​​through the force balance equation;

[0157] In sub-step 3, among the 1000 groups of performance index values, there are 5 fourth-level optional data, 66 third-level optional data, 219 second-level optional data, and 402 fourth-level optional data. 700 data with better performance are selected from them, that is, the screening number is 70% of the predetermined number. The 700 data include all fourth-level optional data, third-level optional data, and second-level optional data, and also include 8 data randomly selected from the remaining data.

[0158] Trace back to find 700 sets of specific blade sizes corresponding to the above 700 sets of performance index values, and count these 700 sets of specific blade sizes as the first-level screening size data;

[0159] Sub-step 4: randomly cross the corresponding relationships of each sub-item in the first-level screening dimension data, and obtain 700 new sets of dimension data, which are counted as the first-level cross dimension data;

[0160] Sub-step 5: Replace the 1000 sets of specific blade sizes given in sub-step 1 with the first-level cross-dimensional data comprising 700 sets of dimension data. Repeat sub-steps 1, 2, and 3 to obtain second-level screening dimension data comprising 490 sets of specific blade sizes. Repeat sub-step 4 again to obtain second-level cross-dimensional data comprising 490 sets of specific blade sizes.

[0161] Sub-step 6: Repeat sub-step 5 three times to obtain five-level cross-dimensional data containing 148 sets of specific blade dimensions;

[0162] When sub-step 5 is repeated for the fourth time, the performance index data obtained for one set of specific blade sizes is:

[0163] Flight time 30min, maximum output power 2kW, maximum flight speed 30m / s, overload 3.06g and take-off weight 5.27k,

[0164] All items in this performance index data are greater than the corresponding values ​​in the expected performance index. This data is five-level optional data, and the specific blade size corresponding to this data can be used to design high-speed multi-rotor blades.

[0165] The specific blade dimensions are:

[0166] The blade diameter is 190, the blade chord length is 30, and the blade torsion angle is 15°.

[0167] The drone was designed and assembled according to the above specific blade dimensions and expected parameters. The flight time was measured to be 32 minutes, with a maximum output power of 2053W, a maximum flight speed of 33.05m / s, an overload of 3.05g, and a takeoff weight of 5.25kg.

[0168] It can be seen that the aircraft designed according to the design method of high-speed multi-rotor blades can meet the expected performance indicators.

[0169] The present invention has been described above with reference to preferred embodiments, but these embodiments are merely exemplary and serve only as illustrations. On this basis, various replacements and improvements can be made to the present invention, all of which fall within the scope of protection of the present invention.

Claims

1. A method for designing a high-speed multi-rotor blade, characterized in that: The method comprises the following steps: Step 1: Determine a preliminary blade size range based on expected parameters; the expected parameters include takeoff weight, fuselage size, flight radius, flight time, and maximum output power; and the blade size includes blade diameter, chord length, and torsion angle. Step 2: establishing an aerodynamic model of the blade according to the preliminary blade size range; Step 3: Establishing a force balance equation for the UAV based on the aerodynamic model of the blades to obtain the relationship between blade size and the performance indicators of the UAV, including flight time, maximum output power, maximum flight speed, overload, and takeoff weight; Step 4: gradually adjusting the blade size through optimization iteration until the blade size can achieve the desired performance indicator; In step 2, the aerodynamic model of the blade includes the following formula (4): Among them, T p Indicates the tension on the blade; H p Indicates the resistance on the blade; Q P Indicates the torque on the blade; represents the pitching moment on the blade; t1, t2, t3, and t4 all represent tension model parameters. Ω represents the rotation speed; V represents the flight speed and the flight speed; α p Indicates the angle between the incoming flow and the blade surface; h1 and h2 both represent resistance model parameters; q1, q2, q3, and q4 all represent torque model parameters; m1, m2, and m3 all represent pitching moment model parameters; In step 3, the force balance equation of the UAV includes the following formula (5): Where m represents the mass of the drone; α represents the angle of attack, θ represents the pitch angle; D F Indicates the fuselage resistance, L F represents the lift of the fuselage; J represents the moment of inertia; represents the pitching moment on the fuselage, T1 represents the pull on the front propeller on the fuselage, T2 represents the pull on the rear propeller on the fuselage, l represents the distance from the center of mass of the blade to the center of mass of the drone, H1 represents the force parallel to the blade generated by the front propeller, H2 represents the force parallel to the blade generated by the rear propeller, d1 represents the diameter of the front propeller, and d2 represents the diameter of the rear propeller; Q p (α, V, Ω1) represents the torque of the front propeller, Q p (α, V, Ω2) represents the torque of the rear propeller; Ω1 represents the rotation speed of the front propeller, and Ω2 represents the rotation speed of the rear propeller; η m (I) represents the motor conversion efficiency; V represents the speed in the x-axis direction, and U represents the speed in the y-axis direction. represents the blade azimuth, P represents the power; When the drone is in a balanced state, The step 4 includes the following sub-steps: Sub-step 1: randomly providing a predetermined number of specific blade sizes; each of the specific blade sizes includes a specific size of a blade diameter, a specific size of a blade chord length, and a specific size of a blade torsion angle; and each of the specific blade sizes falls within the preliminary blade size range; Sub-step 2: for each specific set of blade dimensions, a corresponding set of performance index values ​​is obtained through the force balance equation, thereby obtaining a predetermined number of performance index data; Sub-step 3, selecting some data with better performance from a predetermined number of performance index data, finding the specific blade size corresponding to each set of performance index values, and recording them as the first-level screening size data; Sub-step 4: randomly cross the corresponding relationships of each sub-item in the first-level screening dimension data to obtain first-level cross dimension data; Sub-step 5, replacing the specific blade size randomly given in sub-step 1 with the first-level cross-size data, repeating sub-steps 1, 2, and 3 to obtain second-level screening size data, and then repeating sub-step 4 to obtain second-level cross-size data; Sub-step 6, repeating sub-step 5 multiple times until the performance index obtained in sub-step 2 meets the expected performance index, and recording the blade size value corresponding to the expected performance index; In sub-step 3, the predetermined number of performance indicator data obtained in sub-step 2 are analyzed one by one, and the specific items contained in each set of performance indicator data, namely, the flight time value, the maximum output power value, the maximum flight speed value, the overload value and the take-off weight value, are analyzed. When one value in the item is greater than the corresponding value in the expected performance indicator, the data is first-level optional data; when two values ​​in the item are greater than the corresponding values ​​in the expected performance indicator, the data is second-level optional data; when three values ​​in the item are greater than the corresponding values ​​in the expected performance indicator, the data is third-level optional data; when four values ​​in the item are greater than the corresponding values ​​in the expected performance indicator, the data is fourth-level optional data; when five values ​​in the item are all greater than the corresponding values ​​in the expected performance indicator, the data is fifth-level optional data.

2. The method for designing a high-speed multi-rotor blade according to claim 1, characterized in that: In step 1, the preliminary blade size range is obtained by the following formula (1): R = (1.04r p ~1.21r p ) / sin(180° / n) (1) Where R is the radius of the drone, r p is the propeller radius, and n is the number of propellers.

3. The method for designing a high-speed multi-rotor blade according to claim 1, characterized in that: The number of data with better performance is the screening number, and there is a proportional relationship between the screening number and the predetermined number in sub-step 2, and the screening number is 60-80% of the predetermined number.

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