Methods for calculating the maximum flight speed and flight time of unmanned aerial vehicles (UAVs) and their flight control methods.

Abstract

To overcome the shortcomings of existing UAV flight speed optimization methods, which neglect the influence of noise and vibration, resulting in insufficient robustness of flight speed in real-world complex environments, and the potential for excessive noise or vibration under localized operating conditions, this invention proposes a method for calculating the maximum flight speed and flight time of a UAV, as well as a flight control method. This invention comprehensively integrates factors such as noise intensity and vibration acceleration, establishing acoustic radiation and vibration influence models respectively. These two models are used to solve for the acoustic and vibration-limited speeds, selecting the smaller value as the maximum flight speed of the UAV. The actual maximum flight speed of the UAV is then calculated by combining this with the wind speed and wind angle of the UAV's operating area. When the UAV flies at the actual maximum flight speed obtained by this invention, it not only maintains flight stability and ensures work efficiency but also prevents excessive noise and vibration, avoiding adverse effects of noise and vibration on UAV performance.

Description

Technical Field

[0001] This invention relates to the field of control or regulation systems for non-electrical variables, and specifically to a method for calculating the maximum flight speed and flight time of an unmanned aerial vehicle (UAV) and a flight control method. Background Technology

[0002] As a highly efficient and flexible flight platform, unmanned aerial vehicles (UAVs) are increasingly widely used in various fields such as agricultural monitoring, environmental protection, and logistics transportation. Optimizing their flight performance directly affects mission execution efficiency and reliability. Flight speed is a crucial factor influencing UAV performance; excessively low speeds prolong operation time and increase energy consumption, while excessively high speeds induce stronger aerodynamic noise and structural vibrations, reducing the accuracy of onboard sensors, communication distance, and structural lifespan. Specifically, the coupling relationship between flight speed, noise, and vibration, and their impact on UAV flight performance, are mainly reflected in the following aspects:

[0003] 1. Noise interference:

[0004] The noise generated during drone operation mainly includes the noise from the propeller-vortex interaction caused by propeller rotation and the aerodynamic noise generated by the drone's motion. This noise can interfere with the effective signals of onboard sensors (such as acoustic monitoring equipment), affecting the accuracy of data acquisition. Furthermore, it can impact the communication quality between the drone and the ground station, and may even exceed environmental protection regulations for the drone's operating area. Therefore, in high-precision monitoring tasks requiring near-ground hovering or low-speed cruising, noise has become a significant factor limiting drone flight efficiency.

[0005] 2. Vibration effects:

[0006] When a drone is in operation, vibrations caused by its power system (such as motors and propellers) or external airflow can increase the feedback error of the flight control system, leading to deviations from the flight trajectory. Long-term vibrations can also accelerate the fatigue of the drone's mechanical structure and even cause permanent damage to critical components.

[0007] 3. Dynamic coupling effect:

[0008] Existing research indicates that noise and vibration phenomena often exhibit a nonlinear coupling relationship with flight speed. For example, high-speed flight may exacerbate propeller vortex vibration, while reducing speed may lead to a decrease in the airframe's wind resistance, creating a performance optimization paradox of "speed increase-over-limit" or "speed decrease-instability".

[0009] However, current optimizations of drone performance neglect the above-mentioned aspects, especially the dynamic coupling effect, leading to the following limitations in current optimization schemes:

[0010] 1. For the optimization of flight speed, mainstream research focuses on increasing flight speed or extending flight time, usually ignoring the coupling relationship between noise, vibration and flight speed, resulting in insufficient robustness of the obtained flight speed in real complex environments.

[0011] 2. Regarding the control of noise and vibration, existing technologies focus on the design of noise source elimination devices such as low-noise propellers and vibration suppression devices such as vibration damping structures. Once the design is completed, its noise and vibration suppression effect is fixed, which may lead to excessive noise or vibration under local operating conditions, thereby affecting the performance of the UAV. Summary of the Invention

[0012] To overcome the technical problems of insufficient robustness of flight speed in real complex environments due to neglecting the influence of noise and vibration when optimizing the flight speed of UAVs, and the inability of existing noise and vibration control methods to dynamically adjust the suppression effect, which may lead to excessive noise or vibration under local operating conditions, this invention proposes a method for calculating the maximum flight speed of UAVs.

[0013] Based on the method for calculating the maximum flight speed of a UAV proposed in this invention, this invention further proposes a method for calculating the flight time of a UAV oriented towards path planning and a method for controlling the flight of a UAV.

[0014] The technical solution of this invention is:

[0015] The method for calculating the maximum flight speed of a drone is unique in that it includes the following steps:

[0016] Step 1: Establish the acoustic radiation model and vibration influence model;

[0017] The acoustic radiation model is as follows:

[0018] ;

[0019] The vibration influence model is as follows:

[0020] ;

[0021] In the formula, This refers to the acoustic radiation value. The noise propagation coefficient, This represents the noise figure of the propeller-vortex interaction. This is the aerodynamic noise coupling coefficient; The flight speed of the drone; The propeller speed, , This is the thrust coefficient; The radius of the propeller; This is the cost item for mechanical vibration; The vibration frequency of the drone. ; For the vibration acceleration of the drone, ; This is the vibration sensitivity coefficient. Indicates the vibration frequency of the drone Sensitivity to vibration effects Indicates the vibration acceleration of the drone Sensitivity to vibration effects; The vibration characteristic coefficient, Indicates the vibration frequency of the drone With the flight speed of drones The relationship coefficients Indicates the vibration acceleration of the drone With the flight speed of drones The relationship coefficients between them;

[0022] Step 2: Acquire drone operation data and environmental data;

[0023] The drone's operational data includes propeller radius. Noise propagation coefficient Vibration sensitivity coefficient Thrust coefficient Vibration characteristic coefficient and maximum vibration threshold Noise propagation coefficient Vibration characteristic coefficient Thrust coefficient obtained through wind tunnel testing. Vibration sensitivity coefficient obtained from actual flight tests. The maximum vibration threshold was obtained through numerical simulation. Obtained through vibration testing;

[0024] The environmental data includes the maximum acoustic threshold. Wind speed Wafuu Cape Maximum acoustic threshold Determined according to the environmental protection regulations of the location where the drone is operating; wind speed Wind speed is obtained by deploying wind measurement points in the drone's operating area; wind angle Obtained through route planning software;

[0025] Step 3: Calculate the acoustic limit velocity and the vibration limit velocity;

[0026] Substitute the UAV operation data and environmental data obtained in step 2 into the acoustic radiation model and vibration influence model to solve for the acoustic limit velocity and vibration limit velocity.

[0027] Step 4: Calculate the maximum flight speed:

[0028] The smaller value between the acoustic limit speed and the vibration limit speed is selected as the maximum flight speed. ;

[0029] Step 5: Calculate the actual maximum flight speed:

[0030] Based on the maximum flight speed obtained in step 4 Wind speed obtained in step 3 Wafuu Cape Calculate the actual maximum flight speed .

[0031] Furthermore, in step 2, the UAV path is first divided into multiple sub-paths, and then the UAV operation data and environmental data under each sub-path are acquired; correspondingly, in step 3, the local acoustic limit speed and local vibration limit speed of each sub-path are calculated; in step 4, for each sub-path, the smaller value between its local acoustic limit speed and local vibration limit speed is selected as the local maximum flight speed of each sub-path; in step 5, the local actual maximum flight speed of each sub-path is calculated using the local maximum flight speed of each sub-path, the wind speed and wind angle of each sub-path.

[0032] Furthermore, before step 1, the UAV path is divided into multiple sub-paths, and then the local actual maximum flight speed of each sub-path is solved using the methods in steps 1-5.

[0033] Furthermore, the length of each sub-path Calculate using the following formula:

[0034]

[0035] In the formula, Used as the baseline segment length; Based on the standard segment length When dividing the first The average spacing of obstacles near the path of the segment is obtained through a 3D map; The safe distance for drones is the minimum distance that a drone must maintain from an obstacle while flying. This is a correction factor, with a value ranging from 0 to 1.

[0036] This invention also proposes a method for calculating the flight time of a UAV based on path planning, which is characterized by including the following steps:

[0037] Step 1): Using the above method for calculating the maximum flight speed of the UAV, calculate the local actual maximum flight speed of each sub-path;

[0038] Step 2): Calculate flight time ;

[0039]

[0040] In the formula, For the first The local actual maximum flight speed of the segment path; This represents the total number of sub-paths. This is an empirical parameter, with values ​​ranging from [0,1]. This represents the average distance between obstacles near the total path of the drone.

[0041] This invention also proposes a path planning-oriented UAV flight control method, which is characterized by including the following steps:

[0042] Step 1: Using the above method for calculating the maximum flight speed of the UAV, calculate the local actual maximum flight speed of the UAV on each sub-path, and store the sub-paths and their corresponding local actual maximum flight speeds.

[0043] Step 2: The flight control system controls the UAV's flight based on the local actual maximum flight speed of each sub-path calculated in Step 1.

[0044] The beneficial effects of this invention are:

[0045] 1. The method for calculating the maximum flight speed of a UAV proposed in this invention fully integrates factors such as noise intensity and vibration acceleration. An acoustic radiation model and a vibration influence model are established separately. These two models are used to solve for the acoustic and vibration limiting speeds, and the smaller value is selected as the maximum flight speed of the UAV. Then, the actual maximum flight speed of the UAV is calculated by combining this with the wind speed and wind angle of the UAV's operating area. When the UAV flies at the actual maximum flight speed obtained by this invention, it not only maintains flight stability and ensures work efficiency, but also prevents the noise and vibration generated during UAV flight from exceeding the limits, avoiding the adverse effects of noise and vibration on UAV performance.

[0046] 2. The dynamic relationship between noise, vibration, and flight speed is difficult to describe using a single model. This invention indirectly balances the constraints of noise and vibration on flight speed by taking the minimum value, avoiding the complexity of direct coupling modeling. This makes the established model simple, the calculation process simple, and the required parameters easy to obtain or estimate. It can quickly and accurately provide optimized actual maximum flight speed schemes for UAV flight missions, thereby improving flight stability, work efficiency, safety, and mission completion quality, and providing reliable technical support for the application of UAVs in noise-sensitive and high-precision mission environments.

[0047] 3. The maximum flight speed calculation method for UAVs proposed in this invention further considers the influence of obstacles, divides the total path of the UAV into multiple sub-paths, and calculates the local actual maximum flight speed that is more compatible with the sub-path planning under each sub-path. This ensures that the UAV can take into account flight stability, safety and mission completion quality under each sub-path, and provides a more accurate basis for more precise path planning, time planning, battery management and maintenance of UAVs.

[0048] 4. The UAV flight control method proposed in this invention calculates the local actual maximum flight speed of the UAV under each sub-path, and performs precise flight control of the UAV based on the local actual maximum flight speed, thereby ensuring the flight stability, mission execution efficiency, safety and mission completion quality of the UAV. Attached Figure Description

[0049] Figure 1 This is a flowchart of the method for calculating the maximum flight speed of the UAV according to the present invention.

[0050] Figure 2 This is a flowchart of the method for calculating the maximum flight speed of a UAV based on path planning, as described in this invention.

[0051] Figure 3 This is a flowchart of the UAV flight time calculation method based on path planning according to the present invention.

[0052] Figure 4 This is a flowchart of the UAV flight control method oriented towards path planning according to the present invention. Detailed Implementation

[0053] The present invention will be further described in detail below with reference to the accompanying drawings.

[0054] Reference Figure 1 The method for calculating the maximum flight speed of a drone provided by this invention includes the following steps:

[0055] Step 1: Establish the acoustic radiation model and vibration influence model;

[0056] The acoustic radiation model established in this step is as follows:

[0057] ;

[0058] in, This refers to the acoustic radiation value. The noise propagation coefficient, Characterizing the noise figure of propeller-vortex interaction; Characterizing the aerodynamic noise coupling coefficient; The flight speed of the drone; The propeller speed, , This is the thrust coefficient; The radius of the propeller; This refers to the vortex noise generated by the propeller's rotation; This refers to the aerodynamic noise generated during the flight of a drone.

[0059] The vibration influence model established in this step is as follows:

[0060] ;

[0061] in, This is the cost item for mechanical vibration; The vibration frequency of the drone. ; For the vibration acceleration of the drone, ; The flight speed of the drone; This is the vibration sensitivity coefficient. Indicates the vibration frequency of the drone Sensitivity to vibration effects Indicates the vibration acceleration of the drone Sensitivity to vibration effects; The vibration characteristic coefficient, Indicates the vibration frequency of the drone With the flight speed of drones The relationship coefficients Indicates the vibration acceleration of the drone With the flight speed of drones The relationship coefficients between them; It represents the dominant elastic potential energy term, which is related to the square of the drone's vibration frequency and reflects the periodic elastic potential energy stored in the drone's mechanical system (including the main frame of the drone fuselage, rotor, motor and other components along the vibration transmission path). This represents the dominant inertial force, which is related to the vibration acceleration of the drone and reflects the instantaneous impact of mass inertial force on the main frame structure of the drone fuselage.

[0062] Step 2: Acquire drone operation data and environmental data;

[0063] The drone operational data required for this step includes:

[0064] propeller radius , refers to the distance from the central axis of the drone's propeller to the farthest point of the propeller blade, in meters;

[0065] Noise propagation coefficient ,in, The propeller-vortex interaction noise coefficient is a coefficient representing the relationship between propeller vortex noise and UAV flight status. Characterized by the aerodynamic noise coupling coefficient, which is the coefficient relating aerodynamic noise to the flight speed of the UAV; and Noise data can be obtained through wind tunnel experiments, measuring noise levels at different propeller speeds and wind speeds. The noise data can then be fitted to obtain the desired result. and ; and All are dimensionless quantities;

[0066] Vibration sensitivity coefficient All of these can be obtained through numerical simulation. A three-dimensional model of the UAV is built in simulation software (such as ANSYS), and simulation data of frequency response and acceleration response are obtained. The simulation data is then fitted to obtain the desired results. and ; and All are dimensionless quantities;

[0067] Thrust coefficient The speed of a drone With propeller speed The ratio can be obtained by fitting the acquired data to obtain the propeller speed at different flight speeds of the UAV based on actual flight tests. ; It is a dimensionless quantity;

[0068] Vibration characteristic coefficient All of these can be obtained through wind tunnel experiments, measuring the vibration frequency and acceleration of the UAV under different wind speeds, and fitting the measured data to obtain the results. and ; and All are dimensionless quantities;

[0069] Maximum vibration threshold This refers to the maximum vibration level that a drone can tolerate during flight. Exceeding this threshold may cause structural damage to the drone or affect its flight stability. Maximum vibration threshold. Vibration testing can be used to test a test drone with the same structural parameters as the drone to be performed.

[0070] The environmental data required for this step includes:

[0071] Maximum acoustic threshold This refers to the maximum permissible noise level for a drone during flight; exceeding this threshold may violate relevant noise regulations. The value is determined according to the environmental protection regulations of the location where the drone is operating;

[0072] wind speed Wind speed refers to the horizontal speed of airflow, which can be collected by wind speed measurement points deployed in the drone's operating area, and is measured in meters per second. When there are multiple wind speed measurement points deployed in the drone's operating area, the average wind speed collected from all points is taken as the wind speed. ;

[0073] Wind Corner The wind angle refers to the angle between the ground speed vector and the wind speed vector in the flight speed triangle of a UAV, that is, the angle between the flight path and the wind direction line. The wind angle ranges from 0 to ±180°, and the unit is degrees. It can be obtained by calculation based on ground speed vector and wind speed vector using path planning software.

[0074] Step 3: Calculate the acoustic limit velocity and the vibration limit velocity;

[0075] Based on the acoustic radiation model established in step 1 and the UAV operation data and environmental data obtained in step 2, the acoustically limited speed is obtained. for:

[0076] ;

[0077] Based on the vibration influence model established in step 1 and the UAV operation data obtained in step 2, the vibration limiting velocity is calculated. for:

[0078] .

[0079] Step 4: Calculate the maximum flight speed of the drone;

[0080] Calculate the maximum flight speed of the drone using the following formula :

[0081] .

[0082] Step 5: Calculate the actual maximum flight speed of the drone;

[0083] Based on the maximum flight speed of the drone Combined with the wind speed in the drone operation area Wafuu Cape The actual maximum flight speed of the drone is calculated using the following formula. :

[0084] .

[0085] The above is the basic technical solution of this invention. Based on this, to further improve the dynamic adaptability of this invention to real-time environments, this invention also proposes a method for calculating the maximum flight speed of a UAV based on path planning. (Refer to...) Figure 2 This method first divides the overall path of the UAV into multiple sub-paths, and then calculates the local actual maximum flight speed of each sub-path using the methods described in steps 1-5 above. Alternatively, in step 2 above, the overall path of the UAV can be divided into multiple sub-paths, UAV operation data and environmental data under each sub-path can be obtained, and these can be substituted into the model established in step 1 to solve for the local acoustic limit speed and local vibration limit speed of each sub-path. The smaller value is selected as the maximum flight speed of each sub-path, and then the local actual maximum flight speed of each sub-path is calculated by combining the wind speed and wind angle of the sub-path. Preferably, considering that the wind speed changes significantly in areas with dense obstacles, the influence of obstacles can be considered when dividing the sub-paths. This makes the calculated local actual maximum flight speed of each sub-path more accurate, providing a more accurate basis for estimating the total flight time, mission planning, safety, battery management, and maintenance. Specifically, when considering the influence of obstacles, the sub-path length... Calculate according to the following formula:

[0086]

[0087] In the formula, The base segment length (default is 100 meters, which can be set according to actual flight control requirements) The smaller the value, the higher the flight control precision. Based on the standard segment length When dividing the first The average spacing between obstacles near the path of the segment. It can be obtained through a 3D map; The safe distance for drones is the minimum distance between a drone and an obstacle during flight, which is usually half the drone's wheelbase. This is a correction factor, with a value ranging from 0 to 1.

[0088] Reference Figure 3 This invention also provides a method for calculating the flight time of a UAV based on path planning. First, the method for calculating the maximum flight speed of a UAV based on path planning provided by this invention is used to calculate the local actual maximum flight speed of each sub-path. Then, the local flight time of the UAV on each sub-path is calculated, and finally, the total flight time of the UAV is obtained. The calculation formula is as follows:

[0089]

[0090] In the formula, For the first The local actual maximum flight speed of the segment path; This represents the total number of sub-paths. This is an empirical parameter, with values ​​ranging from [0,1]. The average distance between all obstacles near the total path of the drone; As a correction factor; This is the sum of the local flight times of all sub-paths.

[0091] Reference Figure 4 The present invention also provides a path planning-oriented UAV flight control method. First, the path planning-oriented UAV maximum flight speed calculation method provided by the present invention is used to calculate the local actual maximum flight speed of each sub-path and store it in correspondence with the sub-path. Then, during flight, the flight control system calls the pre-stored local actual maximum flight speed according to the position of the UAV on the sub-path during flight to realize the flight control of the UAV.

[0092] To make the present invention easier to understand, further detailed descriptions are provided below with reference to specific embodiments.

[0093] Example 1:

[0094] In an urban environment, a drone needs to perform a cargo delivery mission. The mission requires the drone to fly at an optimized speed within the urban area, ensuring flight stability while considering the environmental impact of noise. To reduce noise interference to residential areas and improve the drone's lifespan, this embodiment will apply the drone's maximum flight speed calculation method of the present invention to optimize the drone's flight speed.

[0095] The method for calculating the maximum flight speed of the UAV in this embodiment is as follows:

[0096] Step 1: Acquire drone operation data and environmental data;

[0097] Propeller radius: R = 0.5 m; Noise propagation coefficient: =1.2, =0.8; Vibration sensitivity coefficient: =0.5, =0.3; Thrust coefficient: =0.8; Vibration characteristic coefficient: =1, =0.1; Maximum vibration threshold: =35; Maximum acoustic threshold: =60, wind speed: 0.5m / s.

[0098] Step 2: Calculate the acoustic limit velocity and the vibration limit velocity;

[0099] Substituting the UAV operation data and environmental data obtained in step 1 into the acoustic radiation model and vibration influence model established in this invention, the acoustically limited velocity is obtained. and vibration limiting speed They are respectively:

[0100] ;

[0101] .

[0102] Step 3: Calculate the drone's maximum speed ;

[0103] .

[0104] Step 4: Calculate the actual maximum speed of the drone. ;

[0105] Assuming wind angle It is 180°. .

[0106] Therefore, the drone follows the path of this cargo delivery mission. At the maximum flight speed, it can ensure that the noise and vibration generated during flight will not exceed the standard.

[0107] Example 2:

[0108] This embodiment is based on embodiment 1, but divides the total path of embodiment 1 into multiple sub-paths and further calculates the UAV flight time.

[0109] Assuming the total path length is 3000m, based on the baseline segment length... When dividing the path, the average spacing between obstacles near each segment is equal. =50m, correction factor =0.8, =20m, then the length of each sub-path for:

[0110] .

[0111] In practice, the maximum acoustic threshold and maximum vibration threshold may differ for different sub-paths, and the local maximum flight speed calculated using the method of this invention may also differ. For ease of calculation, this embodiment assumes that the local maximum flight speed for each sub-path segment is the same as that calculated in Example 1. , If we take 0.6, then when performing the cargo delivery task in Example 1, the drone flight time is:

[0112]

[0113] Therefore, for the drone to complete the cargo delivery task in this embodiment, while ensuring flight stability, noise, and vibration do not exceed the limits, the drone's flight time is [time missing]. Second.

[0114] Example 3:

[0115] This embodiment is based on embodiment 2. The actual local maximum flight speeds calculated in embodiment 2 for each sub-path are stored in the flight control system. The flight control system calls the corresponding actual local maximum flight speed according to the sub-path to perform precise flight control on the UAV, so that the UAV can fly stably in each sub-path and ensure that the maximum acoustic threshold and the maximum vibration threshold are not exceeded, thus improving its adaptability to dynamic environments.

Claims

1. A method for calculating the maximum flight speed of a UAV, characterized in that, Including the following steps: Step 1: Establish the acoustic radiation model and vibration influence model; The acoustic radiation model is as follows: ； The vibration influence model is as follows: ； In the formula, This refers to the acoustic radiation value. The noise propagation coefficient, This represents the noise figure of the propeller-vortex interaction. This is the aerodynamic noise coupling coefficient; The flight speed of the drone; The propeller speed, , This is the thrust coefficient; The radius of the propeller; This is the cost item for mechanical vibration; The vibration frequency of the drone. ; For the vibration acceleration of the drone, ; This is the vibration sensitivity coefficient. Indicates the vibration frequency of the drone Sensitivity to vibration effects Indicates the vibration acceleration of the drone Sensitivity to vibration effects; The vibration characteristic coefficient, Indicates the vibration frequency of the drone With the flight speed of drones The relationship coefficients Indicates the vibration acceleration of the drone With the flight speed of drones The relationship coefficients between them; Step 2: Acquire drone operation data and environmental data; The drone's operational data includes propeller radius. Noise propagation coefficient Vibration sensitivity coefficient Thrust coefficient Vibration characteristic coefficient and maximum vibration threshold Noise propagation coefficient Vibration characteristic coefficient Thrust coefficient obtained through wind tunnel testing; Vibration sensitivity coefficient obtained from actual flight tests. The maximum vibration threshold was obtained through numerical simulation. Obtained through vibration testing; The environmental data includes the maximum acoustic threshold. Wind speed Wafuu Cape Maximum acoustic threshold Determined according to the environmental protection regulations of the location where the drone is operating; wind speed Wind speed is obtained by deploying wind measurement points in the drone's operating area; wind angle Obtained through route planning software; Step 3: Calculate the acoustic limit velocity and the vibration limit velocity; Substitute the UAV operation data and environmental data obtained in step 2 into the acoustic radiation model and vibration influence model to solve for the acoustic limit velocity and vibration limit velocity. Step 4: Calculate the maximum flight speed: The smaller value between the acoustic limit speed and the vibration limit speed is selected as the maximum flight speed. ; Step 5: Calculate the actual maximum flight speed: Based on the maximum flight speed obtained in step 4 Wind speed obtained in step 3 Wafuu Cape Calculate the actual maximum flight speed .

2. The method for calculating the maximum flight speed of a UAV according to claim 1, characterized in that, In step 2, the UAV path is first divided into multiple sub-paths, and then the UAV operation data and environmental data under each sub-path are acquired. Correspondingly, in step 3, the local acoustic limit speed and local vibration limit speed of each sub-path are calculated. In step 4, for each sub-path, the smaller value between its local acoustic limit speed and local vibration limit speed is selected as the local maximum flight speed of each sub-path. In step 5, the local actual maximum flight speed of each sub-path is calculated using the local maximum flight speed of each sub-path, the wind speed and wind angle of each sub-path.

3. The method for calculating the maximum flight speed of a UAV according to claim 1, characterized in that, Before step 1, the UAV path is divided into multiple sub-paths. Then, for each sub-path, the local actual maximum flight speed of each sub-path is calculated using the methods in steps 1-5.

4. The method for calculating the maximum flight speed of a UAV according to claim 2 or 3, characterized in that, Length of each subpath Calculate using the following formula: In the formula, Used as the baseline segment length; Based on the standard segment length When dividing the first The average spacing of obstacles near the path of the segment is obtained through a 3D map; The safe distance for drones is the minimum distance that a drone must maintain from an obstacle while flying. This is a correction factor, with a value ranging from 0 to 1.

5. A method for calculating UAV flight time based on path planning, characterized in that, Includes the following steps: Step 1): Using the maximum flight speed calculation method for UAVs as described in any of claims 2-4, calculate the local actual maximum flight speed of each sub-path; Step 2): Calculate flight time ; In the formula, For the first The local actual maximum flight speed of the segment path; This represents the total number of sub-paths. This is an empirical parameter, with values ​​ranging from [0,1]. This represents the average distance between obstacles near the total path of the drone.

6. A path-planning-oriented UAV flight control method, characterized in that, Includes the following steps: Step 1: Using the method for calculating the maximum flight speed of the UAV as described in any one of claims 2-4, calculate the local actual maximum flight speed of the UAV on each sub-path, and store the sub-paths and their corresponding local actual maximum flight speeds. Step 2: The flight control system controls the UAV's flight based on the local actual maximum flight speed of each sub-path calculated in Step 1.

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