Method and system for evaluating regional residence capability of long-endurance aircraft

Abstract

The invention discloses a method and a system for evaluating the regional residence capability of a long-endurance aircraft, and belongs to the technical field of aerospace. According to the method, based on battery parameters, solar radiation and historical data of a wind field, an airspeed time change rule of the long-endurance aircraft which meets day and night energy circulation and maximally utilizes solar energy is determined through a nested optimization algorithm; combining the airspeed and the wind speed vector to synthesize the ground speed, updating the position by adopting a fixed time step length, and iteratively solving the farthest distance of the residence point capable of going back and forth in the specified time in each direction through a dichotomy method; and finally, a closed circle is defined by the farthest points in all the directions, and quantitative evaluation of the long-endurance aircraft area residence capability is achieved. According to the method, the all-day optimal airspeed change of the long-endurance aircraft is determined through the nested optimization algorithm, and the farthest residence point in each direction is iteratively solved in combination with vector calculation and the dichotomy, so that the problem of lack of an effective evaluation method for the regional residence capability of the long-endurance aircraft in the prior art is solved; and an important basis can be provided for task planning and performance optimization of the long-endurance aircraft.

Description

Technical Field

[0001] This invention relates to the field of aerospace technology, specifically to a method and system for assessing the regional loiter capability of long-endurance aircraft. Background Technology

[0002] Long-endurance vehicles (LEVs) are high-altitude unmanned aerial vehicles capable of performing tasks such as deep space exploration, Earth observation, and communication services in the stratosphere, and have broad application value. The regional deployment capabilities of LEVs enable dynamic area coverage and flexibly respond to the immediate needs of scenarios such as multi-target monitoring and emergency communication.

[0003] However, there is currently no corresponding capability assessment method for the area-keeping capability of long-endurance aircraft. Long-endurance aircraft have a large area-keeping maneuvering range, do not need to constantly contend with all airflows, and can achieve "energy-saving maneuvers" especially when in the direction of the airflow.

[0004] There is currently no scientific and unified evaluation methodology for the regional stationing capability of long-endurance aircraft. This gap in evaluation stems from the complexity of regional stationing capability: it involves not only the "stationing area" but also multiple dynamic variables such as "energy efficiency under different wind field and airflow conditions" and "the adaptability of energy recycling capability to stationing duration." Existing research mainly focuses on the technical implementation of regional stationing, such as airflow utilization and path planning, but has not constructed a comprehensive evaluation framework covering "performance – external wind field – energy recycling." This results in an inability to accurately and comprehensively evaluate the regional stationing capability of long-endurance aircraft, thereby affecting the mission planning, performance optimization, and application promotion of long-endurance aircraft. Summary of the Invention

[0005] This invention provides a method and system for assessing the regional loiter capability of long-endurance aircraft, enabling a scientific and accurate quantitative assessment of the regional loiter capability of long-endurance aircraft, and providing a reliable basis for mission planning and design optimization of long-endurance aircraft.

[0006] To achieve the above objectives, the present invention provides the following technical solution: This invention protects a method for assessing the area loiter capability of a long-endurance aircraft, comprising the following steps: Collect the basic data required for the assessment, including battery capacity, minimum permissible battery SOC, start time and location of long-endurance aircraft regional stay, historical solar radiation energy data, and historical wind field data. Based on the aforementioned basic data, the variation pattern of the optimal airspeed of the long-endurance aircraft throughout the day with time is calculated using a nested optimization algorithm. By combining airspeed variation patterns with wind field data, the dynamic changes in ground speed of long-endurance aircraft with time and position are obtained through vector calculation; The farthest dwelling point that can be reached and returned to the dwelling point in each direction within a specified time is solved by the bisection method iteratively. A closed circle is formed by the farthest dwelling points in each direction, and the closed circle represents the regional dwelling capability of the long-endurance aircraft.

[0007] Furthermore, the calculation of the aircraft's optimal airspeed over time using a nested optimization algorithm specifically includes: The day is divided into five phases: the first part of night, the transition from night to day, daytime, the transition from day to night, and the second part of night. Calculate the solar power supply capacity at different times based on the formula for solar panel output power; Calculate the actual power consumption at different speeds based on the power consumption formula for stable flight of long-endurance aircraft; With the goal of maximizing the solar energy utilization efficiency throughout the day, the optimal daytime speed and the corresponding optimal nighttime speed are determined through a nested optimization algorithm. At the same time, the speed during the transition phase is calculated to obtain the variation law of the sky speed over time throughout the day. The optimization constraint is that the SOC of the battery at any time is not lower than the minimum allowable SOC value.

[0008] Furthermore, the nested algorithm specifically includes: Given an initial daytime speed, under the condition that Under the constraints, The objective is to minimize the optimal nighttime speed, where... This represents the actual power consumption at night. Nighttime duration, This is the minimum permissible SOC value for the battery. For battery capacity, To store energy for the battery all day long, This refers to the energy consumed by the spacecraft throughout the day; by With the goal of maximizing, the daytime speed is iteratively updated to obtain the optimal daytime speed and the corresponding optimal nighttime speed that maximizes the solar energy utilization efficiency throughout the day. The duration of each stage is divided according to the relationship between solar power supply capacity and actual power consumption, the speed of the transition stage is determined, and a complete all-day sky speed change curve is formed.

[0009] Furthermore, the dynamic change of the aircraft's ground speed with time and position is obtained through vector calculation by combining airspeed variation patterns and wind field data, specifically including: Based on the principle of vector composition, by Vector method for calculating the magnitude of ground velocity: in, The angle between wind speed and ground speed. The angle between wind speed and ground speed. Airspeed, For wind speed, For ground speed.

[0010] Furthermore, the step of iteratively solving for the farthest dwelling point that can be reached and returned to within a specified time in each direction using the bisection method specifically includes: With a fixed ground velocity direction, based on a fixed time step ,pass Update position and calculate the specified time. The farthest distance that can be reached inside ; Take the initial return test distance When the aircraft arrived When flying in the opposite direction, determine the specified time. Is it possible to return to the base within the area? If it cannot be returned, then update. ; If it can be returned, then update. The process is iterated until convergence, yielding the farthest dwell point that meets the requirements in the stated direction.

[0011] Furthermore, the closed circle formed by the farthest dwelling points in each direction, which characterizes the regional dwelling capability of the long-endurance aircraft, includes: By uniformly dividing the 360° direction, the farthest dwell point in each division direction is determined, and a closed loop is formed by connecting all the farthest dwell points. The coverage area of ​​the closed loop is the boundary of the regional dwelling capability of the long-endurance aircraft.

[0012] In another aspect, the present invention claims protection for a long-endurance aircraft area loiter capability assessment system, comprising: The data acquisition module is used to collect data on battery capacity, minimum permissible battery SOC, the start time and location of long-endurance aircraft's regional stay, historical solar radiation energy data, and historical wind field data. The airspeed optimization module is used to calculate the variation of the aircraft's optimal airspeed over time based on the day-night energy cycle constraint and through a nested optimization algorithm. The ground speed calculation module is used to combine airspeed variation patterns with wind field data to obtain the dynamic changes of the aircraft's ground speed with time and position through vector calculation; The module for finding the farthest dwelling point is used to iteratively solve for the farthest dwelling point that can be reached and returned to the dwelling point in each direction within a specified time using the bisection method; The evaluation result generation module is used to output the regional dwelling capability evaluation results of long-endurance aircraft by forming a closed circle with the farthest dwelling points in each direction.

[0013] Furthermore, the airspeed optimization module includes: The phase division module is used to divide a day into five phases: the first part of night, the transition from night to day, daytime, the transition from day to night, and the second part of night. The solar power calculation unit is used to calculate the solar power supply capacity at different times based on the solar panel output power formula. The power consumption calculation unit is used to calculate the actual power consumption at different speeds based on the power consumption formula for stable flight of a long-endurance aircraft. The optimization solution unit is used to determine the optimal airspeed variation pattern through a nested optimization algorithm with the goal of maximizing the solar energy utilization efficiency throughout the day.

[0014] Furthermore, the farthest dwell point solution module includes a direction splitting unit and a bisection iteration unit, wherein the direction splitting unit is used to uniformly split the 360° direction; The bisection iterative unit is used to solve for the farthest dwell point that can be reached and returned to the dwell point within a specified time for each split direction by using the bisection iterative method.

[0015] In another aspect, the present invention protects a computer-readable storage medium storing a computer program that, when executed by a processor, implements any of the methods described above.

[0016] Technical effects of the present invention Compared with the prior art, the present invention has the following advantages: (1) This invention constructs a comprehensive evaluation framework covering “performance-external wind field-energy cycle”, fills the gap in the evaluation of the regional dwelling capability of long-endurance aircraft in the prior art, and realizes the scientific quantitative evaluation of regional dwelling capability; (2) By using a nested optimization algorithm to determine the optimal airspeed variation pattern, the day and night energy cycle is guaranteed, and the utilization of solar energy is maximized, thereby improving the accuracy and rationality of the assessment. (3) The ground speed is calculated by vector synthesis and the farthest point is solved by bisection method. The dynamic interference of wind field is taken into account, which can accurately reflect the difference in dwell capacity in different directions. (4) The evaluation results are presented in a closed loop format, which is intuitive and clear, and can provide reliable data support for mission planning, path design and performance optimization of long-endurance aircraft.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention.

[0018] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0019] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of a method for assessing the regional loiter capability of a long-endurance aircraft in an embodiment of the present invention; Figure 2 This is a schematic diagram of the farthest dwelling point and the closed loop in each direction in an embodiment of the present invention; Figure 3 This is a schematic diagram of a long-endurance aircraft area dwell capability assessment system according to an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] Example 1 This invention provides a method and system for evaluating the regional loiter capability of long-endurance aircraft by combining regional loiter range, external wind field interference, and energy cycle. The regional loiter capability of the aircraft is evaluated by a closed circle formed by the farthest points that the long-endurance aircraft can reach and return to the loiter point in different directions within a specified time. That is, the long-endurance aircraft can reach and return to the loiter point from any point within the closed circle within the specified time.

[0023] To achieve the above objectives, the present invention provides the following solution: Figure 1 The diagram shows a flowchart of a method for assessing the area loitering capability of a long-endurance aircraft according to the present invention, which includes the following steps: Step 1: Collect basic data, including: battery capacity, minimum permissible battery SOC, time and location of long-endurance aircraft's regional stay, historical data on solar radiation energy, and historical data on wind fields.

[0024] Step 2: Calculate the optimal airspeed variation pattern throughout the day Based on the day-night energy cycle constraint, a nested optimization algorithm is used to calculate the variation of the aircraft's optimal airspeed over time throughout the day, ensuring maximum solar energy utilization and that the battery SOC never falls below the minimum allowable value. The specific process is as follows: 1. Stage Division: Starting from 0:00, the day is divided into five stages: the first part of night, the transition from night to day, daytime, the transition from day to night, and the second part of night. Assuming the speed during daytime and nighttime... Given the data, the actual power consumption during the day and night can be calculated using equations (1.2, 1.3). .

[0025] 1) When At that time, the daytime phase begins. Then it enters the nighttime phase. This is the transition phase. Therefore, we can understand that battery energy will be consumed during the nighttime phase, while the transition phase can utilize only solar power for speed transition. This allows us to calculate the speed of the transition phase, during which energy will be stored in the battery during the daytime phase.

[0026] 2. Calculation of Solar Power Supply Capacity This study calculates how the speed of a long-endurance aircraft should vary throughout the day to maximize solar energy utilization, while ensuring a diurnal energy cycle. After determining the start time and location of the aircraft's regional stay and its duration, historical data on solar radiation at the corresponding time and location are retrieved, and the output power of the solar panels is calculated using the following formula. (1.1) in, The total area of ​​the solar panels. The photoelectric conversion efficiency of a solar panel. This refers to solar radiation.

[0027] 3. Power Consumption Calculation for Long-Endurance Aircraft: During stable flight, the power consumption of a long-endurance aircraft is related to its speed by the following condition: (1.2) (1.3) in, This represents the actual power consumption. For motor efficiency, Airspeed, air density, The drag coefficient, For reference area.

[0028] Meeting the energy cycle requirement means that the SOC of a long-endurance aircraft battery at any given time is not lower than the minimum allowable SOC value. When the energy stored in the battery throughout the day can be consumed as much as possible, the efficiency of solar energy utilization is considered to be maximized.

[0029] 4. Nested optimization method for finding the optimal airspeed: 1) Calculate the total energy consumed by the long-endurance aircraft throughout the day. (1.4) in, Total nighttime duration Total daytime duration MT This represents the total duration of the transition phase.

[0030] 2) The battery's total energy storage for the entire day is: (1.5) in, AT Indicates the whole day. DT Indicates daytime period, NT Indicates the nighttime period. MT Indicates the time period of the transition phase. Indicates battery capacity.

[0031] 3) Given a daytime speed, under the premise that the battery SOC does not fall below the allowable value, i.e. It can be determined that each nighttime speed value corresponds to a and ,by With the objective in mind, we can find the nighttime speed value that minimizes its value.

[0032] 4) First level of optimization: As shown in 3), the optimal nighttime speed can be calculated based on different daytime speeds, thus ensuring that each daytime speed value corresponds to a specific nighttime speed. So at this point With the objective being to find the daytime speed that maximizes its value, we can obtain the value of that speed.

[0033] 5) Second optimization: The nested optimization algorithm described above can be used to find the daytime speed that maximizes the solar energy utilization efficiency throughout the day and its corresponding nighttime speed.

[0034] 6) Transition phase speed calculation: The transition phase only uses solar power for speed transition. That is, the airspeed of the transition phase can be calculated by combining formulas (1.2) and (1.3), and finally the change law of the airspeed over time covering the five phases is formed.

[0035] Based on 1), the time periods of daytime, nighttime, and transition phases are determined, and the airspeed changes over time are obtained. The aircraft uses this airspeed change over time as a standard, which can satisfy the energy cycle throughout the day and maximize the utilization of solar energy.

[0036] Step 3: Calculate the dynamic changes in ground velocity. The calculated daily speed variations that maximize energy efficiency at different locations and times are used as the basis for assessing the long-endurance aircraft's area loiter capability. This is combined with the airspeed variation patterns obtained in step two. Based on wind field data and the principle of vector synthesis, the dynamic changes in ground speed of the long-endurance aircraft with time and location are calculated, as follows: 1) With a fixed ground speed direction, for a known time and location, retrieve the wind speed at the corresponding time and location, and then use the airspeed calculated in step two. At this point, the known variables are the magnitude of the airspeed, the direction of the ground speed, and the magnitude and direction of the wind speed. The magnitude of ground velocity is calculated using a vector method. (1.6) in, The angle between wind speed and ground speed. The angle between wind speed and ground speed. This represents the magnitude of the ground speed.

[0037] 2) The ground speed at different times and locations can be obtained from the calculation in 1). When a long-endurance aircraft is stationary in a region, its time and location also change. Therefore, the ground speed of the aircraft changes at every moment. A fixed time step is adopted. The distance in a fixed direction The time and location will be updated in each step of the solution process. It will also be updated.

[0038] Step 4: Solve for the farthest dwelling points in each direction Using the position update formula in 2), calculate the specified time. The farthest distance that internal energy can reach Using the binary search method, take ,when When the ground speed direction reverses, the spacecraft returns along the same route, updating its position in the same way as in 2), and determining the time. Will the aircraft be able to reach the point? And then they returned to their base.

[0039] 3) Iteratively update the returned test distance: if time If you cannot return to your base, then update. Conversely, update to Update using a binary search method The value is used to determine whether it is possible to reach the point and return to the dwell point, and finally the farthest dwell point that meets the requirements in this direction is obtained.

[0040] Step 5: Generate the regional residency capacity assessment results Calculate the farthest dwelling point that meets the requirements in each direction (dividing 360°) (the dwelling point can be reached and returned in this direction within a specified time). Then connect the farthest dwelling points in each direction in order of direction to form a closed circle. The coverage area of ​​this closed circle is the boundary of the area dwelling capability of the long-endurance aircraft, which represents the area dwelling capability of the long-endurance aircraft. Figure 2 This is a schematic diagram of the farthest dwelling point and closed loop in each direction according to the present invention.

[0041] Example 2 Figure 3 The present invention also provides a schematic diagram of a long-endurance aircraft area loiter capability assessment system, the system comprising: The data acquisition module is used to collect data on battery capacity, minimum allowable battery SOC, the start time and location of long-endurance aircraft's regional stay, historical solar radiation energy data, and historical wind field data, and to preprocess the data (such as format conversion and outlier removal). The airspeed optimization module includes a stage division unit, a solar power calculation unit, a power consumption calculation unit, and an optimization solution unit. It is used to calculate the variation of the optimal airspeed of a long-endurance aircraft throughout the day with time based on the day-night energy cycle constraint and through a nested optimization algorithm. The ground speed calculation module is used to combine airspeed variation patterns and wind field data to obtain the dynamic changes in ground speed of long-endurance aircraft over time and location through vector calculation, and to update the ground speed data in real time. The module for finding the farthest dwell point includes a direction splitting unit and a bisection iteration unit. The direction splitting unit is used to uniformly split the 360° direction, and the bisection iteration unit is used to solve the farthest dwell point that can be reached and returned to the dwell point within a specified time for each split direction by using the bisection iteration method. The assessment results generation module is used to generate a visualized regional dwelling capacity assessment report by forming a closed circle from the farthest dwelling points in each direction, and outputting the geometric parameters of the closed circle (such as area, maximum radius, and minimum radius) and the corresponding assessment conclusions.

[0042] In another aspect, the present invention protects a computer-readable storage medium storing a computer program that, when executed by a processor, implements any of the methods described above.

[0043] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0044] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for assessing the regional loiter capability of a long-endurance aircraft, characterized in that, Includes the following steps: Collect the basic data required for the assessment, including battery capacity, minimum permissible battery SOC, start time and location of the aircraft’s regional stay, historical solar radiation energy data, and historical wind field data. Based on the aforementioned basic data, the variation pattern of the optimal airspeed of the long-endurance aircraft throughout the day with time is calculated using a nested optimization algorithm. By combining the airspeed variation pattern with wind field data, the dynamic change of the ground speed of the aircraft with time and position is obtained through vector calculation; The farthest dwelling point that can be reached and returned to the dwelling point in each direction within a specified time is solved by the bisection method iteratively. A closed circle is formed by the farthest dwelling points in each direction, and the closed circle represents the regional dwelling capability of the long-endurance aircraft.

2. The method for assessing the regional loiter capability of long-endurance aircraft according to claim 1, characterized in that, The calculation of the variation of the optimal airspeed of a long-endurance aircraft throughout the day with time using a nested optimization algorithm specifically includes: The day is divided into five phases: the first part of night, the transition from night to day, daytime, the transition from day to night, and the second part of night. Calculate the solar power supply capacity at different times based on the formula for solar panel output power; Calculate the actual power consumption at different speeds based on the power consumption formula for stable flight of long-endurance aircraft; With the goal of maximizing the solar energy utilization efficiency throughout the day, the optimal daytime speed and the corresponding optimal nighttime speed are determined through a nested optimization algorithm. At the same time, the speed during the transition phase is calculated to obtain the variation law of the sky speed over time throughout the day. The optimization constraint is that the SOC of the battery at any time is not lower than the minimum allowable SOC value.

3. The method for assessing the area loiter capability of long-endurance aircraft according to claim 2, characterized in that, The nested algorithm specifically includes: Given an initial daytime speed, under the condition that Under the constraints, The objective is to minimize the optimal nighttime speed, where... This represents the actual power consumption at night. Nighttime duration, This is the minimum permissible SOC value for the battery. For battery capacity, To store energy for the battery all day long, This refers to the energy consumed by the spacecraft throughout the day; by With the goal of maximizing, the daytime speed is iteratively updated to obtain the optimal daytime speed and the corresponding optimal nighttime speed that maximizes the solar energy utilization efficiency throughout the day. The duration of each stage is divided according to the relationship between solar power supply capacity and actual power consumption, the speed of the transition stage is determined, and a complete all-day sky speed change curve is formed.

4. The method for assessing the area loiter capability of long-endurance aircraft according to claim 1, characterized in that, The dynamic changes in ground speed of a long-endurance aircraft with time and position are obtained through vector calculation by combining airspeed variation patterns and wind field data. Specifically, this includes: Based on the principle of vector composition, by Vector method for calculating the magnitude of ground velocity: in, The angle between wind speed and ground speed. The angle between wind speed and ground speed. Airspeed, For wind speed, For ground speed.

5. The method for assessing the regional loiter capability of long-endurance aircraft according to claim 1, characterized in that, The method of iteratively solving for the farthest dwell point that can be reached and returned to within a specified time in each direction using the bisection method specifically includes: With a fixed ground velocity direction, based on a fixed time step ,pass Update position and calculate the specified time. The farthest distance that can be reached inside ; Take the initial return test distance When the aircraft arrived When flying in the opposite direction, determine the specified time. Is it possible to return to the base within the area? If it cannot be returned, then update. ; If it can be returned, then update. The process is iterated until convergence, yielding the farthest dwell point that meets the requirements in the stated direction.

6. The method for assessing the area loiter capability of a long-endurance aircraft according to claim 1, characterized in that, The closed circle formed by the farthest dwelling points in each direction, representing the regional dwelling capability of the long-endurance aircraft, includes: By uniformly dividing the 360° direction, the farthest dwell point in each division direction is determined, and a closed loop is formed by connecting all the farthest dwell points. The coverage area of ​​the closed loop is the boundary of the regional dwelling capability of the long-endurance aircraft.

7. A system for assessing the area loiter capability of a long-endurance aircraft, characterized in that, include: The data acquisition module is used to collect data on battery capacity, minimum permissible battery SOC, the start time and location of long-endurance aircraft's regional stay, historical solar radiation energy data, and historical wind field data. The airspeed optimization module is used to calculate the variation of the aircraft's optimal airspeed over time throughout the day using a nested optimization algorithm, based on the day-night energy cycle constraint. The ground speed calculation module is used to combine airspeed variation patterns and wind field data to obtain the dynamic changes of the aircraft's ground speed with time and location through vector calculation. The module for finding the farthest dwelling point is used to iteratively solve for the farthest dwelling point that can be reached and returned to the dwelling point in each direction within a specified time using the bisection method; The evaluation result generation module is used to output the regional dwelling capability evaluation results of long-endurance aircraft by forming a closed circle with the farthest dwelling points in each direction.

8. The long-endurance aircraft area loiter capability assessment system according to claim 7, characterized in that, The airspeed optimization module includes: The phase division module is used to divide a day into five phases: the first part of night, the transition from night to day, daytime, the transition from day to night, and the second part of night. The solar power calculation unit is used to calculate the solar power supply capacity at different times based on the solar panel output power formula. The power consumption calculation unit is used to calculate the actual power consumption at different speeds based on the power consumption formula for stable flight of a long-endurance aircraft. The optimization solution unit is used to determine the optimal airspeed variation pattern through a nested optimization algorithm with the goal of maximizing the solar energy utilization efficiency throughout the day.

9. The long-endurance aircraft area loiter capability assessment system according to claim 7, characterized in that, The farthest dwell point solution module includes a direction splitting unit and a bisection iteration unit. The direction splitting unit is used to uniformly split the 360° direction. The bisection iterative unit is used to solve for the farthest dwell point that can be reached and returned to the dwell point within a specified time for each split direction by using the bisection iterative method.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements a method for assessing the area loiter capability of a long-endurance aircraft according to any one of claims 1-6.

Images