CN115906275A - Method for rapidly evaluating energy distribution of solar aircraft based on GUI visualization - Google Patents
Method for rapidly evaluating energy distribution of solar aircraft based on GUI visualization Download PDFInfo
- Publication number
- CN115906275A CN115906275A CN202211345095.1A CN202211345095A CN115906275A CN 115906275 A CN115906275 A CN 115906275A CN 202211345095 A CN202211345095 A CN 202211345095A CN 115906275 A CN115906275 A CN 115906275A
- Authority
- CN
- China
- Prior art keywords
- aircraft
- solar
- photovoltaic cell
- parameters
- flight
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000012800 visualization Methods 0.000 title claims abstract description 24
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 12
- 238000012546 transfer Methods 0.000 claims abstract description 10
- 238000010168 coupling process Methods 0.000 claims abstract description 9
- 238000005859 coupling reaction Methods 0.000 claims abstract description 9
- 230000002068 genetic effect Effects 0.000 claims abstract description 8
- 238000005457 optimization Methods 0.000 claims description 25
- 230000008569 process Effects 0.000 claims description 20
- 230000005855 radiation Effects 0.000 claims description 20
- 230000004907 flux Effects 0.000 claims description 12
- 238000004088 simulation Methods 0.000 claims description 9
- 230000009194 climbing Effects 0.000 claims description 8
- 230000001133 acceleration Effects 0.000 claims description 7
- 238000009434 installation Methods 0.000 claims description 7
- 230000009466 transformation Effects 0.000 claims description 7
- 230000014509 gene expression Effects 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 4
- 241001175904 Labeo bata Species 0.000 claims description 3
- 239000003990 capacitor Substances 0.000 claims description 3
- 238000007599 discharging Methods 0.000 claims description 3
- 238000006073 displacement reaction Methods 0.000 claims description 3
- 238000005265 energy consumption Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims 1
- 230000008859 change Effects 0.000 abstract description 7
- 230000008878 coupling Effects 0.000 abstract description 6
- 230000001105 regulatory effect Effects 0.000 abstract description 2
- 210000004027 cell Anatomy 0.000 description 82
- 238000011160 research Methods 0.000 description 7
- 238000007726 management method Methods 0.000 description 6
- 238000004146 energy storage Methods 0.000 description 5
- 238000011156 evaluation Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000004134 energy conservation Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 229910052739 hydrogen Inorganic materials 0.000 description 2
- 239000001257 hydrogen Substances 0.000 description 2
- 230000035772 mutation Effects 0.000 description 2
- UJCHIZDEQZMODR-BYPYZUCNSA-N (2r)-2-acetamido-3-sulfanylpropanamide Chemical compound CC(=O)N[C@@H](CS)C(N)=O UJCHIZDEQZMODR-BYPYZUCNSA-N 0.000 description 1
- 241001669680 Dormitator maculatus Species 0.000 description 1
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 239000002803 fossil fuel Substances 0.000 description 1
- 150000002431 hydrogen Chemical class 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005381 potential energy Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Landscapes
- Photovoltaic Devices (AREA)
Abstract
The invention provides a method for quickly evaluating energy distribution of a solar aircraft based on GUI visualization, which comprises the steps of predicting the surface temperature of a photovoltaic cell by utilizing a heat transfer model of the surface of a wing to obtain the surface temperature change of the photovoltaic cell; the method comprises the following steps of (1) researching the real-time state and input and output conditions of each energy flow system by constructing a multi-system strong coupling solar aircraft energy flow model; the flight trajectory of the aircraft is regulated and optimized by using a genetic algorithm and taking the thrust, the attack angle and the roll angle as independent variables, so that the energy distribution condition and the flight performance of the solar aircraft are improved. The method has stronger applicability, and is suitable for calculating and optimizing the energy distribution of the solar aircraft with any parameter and under different flight states in a three-dimensional space.
Description
Technical Field
The invention belongs to the technical field of aerospace, and particularly relates to a method for quickly evaluating energy distribution of a solar aircraft based on GUI visualization.
Background
The solar aircraft has the advantages of cleanness, no pollution and the like, breaks through the range and altitude limit of the fossil fuel aircraft, and has extremely high application value. The solar aircraft converts solar radiation energy into electric energy through the photovoltaic module, part of the electric energy is supplied to the electric propulsion system to generate thrust to maintain the air-lag flight and the normal operation of electronic equipment, and the rest electric energy is stored in the secondary battery for cruise at night. The photovoltaic conversion efficiency of the photovoltaic module is controlled by solar energy, the electronic equipment needs reasonable energy supply, and the energy distribution needs to be changed from time to time in the flight attitude cruise process of the aircraft. Therefore, the total engine energy distribution will directly affect the overall efficiency.
The systems involved in the energy flow of solar aircraft are numerous, with the interplay between the atmospheric environment, the photovoltaic cell system, the battery system, the power system and the motion of the aircraft itself. Therefore, a solar aircraft energy component model considering different actual working conditions needs to be constructed.
Of all systems that participate in the flow of energy, photovoltaic cells are most strongly influenced by the environment. Firstly, the photovoltaic cell can only utilize the component of solar radiation vertical to the cell surface, and the traditional expression method for calculating the solar incident ray vector is limited in a ground coordinate system and is insufficient in consideration of the aircraft attitude; secondly, the output of the photovoltaic cell is related to the actual surface temperature thereof, and as the photovoltaic cell converts most of solar energy into heat energy when generating electric energy, the surface temperature of the photovoltaic cell is not completely equal to the ambient temperature, so that modeling research on the input and output of the photovoltaic cell under different conditions is necessary.
At present, the conversion rate of a photovoltaic cell is low, energy supply under different environmental conditions is unstable, the energy storage of a storage battery is limited due to the limitation of self capacity, in order to ensure sufficient energy supply in the flight process of an aircraft and realize long-endurance flight of the solar aircraft, how to manage and distribute the energy is one of important problems to be considered in the design of the aircraft, and predicting the energy distribution of the whole aircraft and optimizing the existing flight working conditions are the necessary way for researching the process of the solar aircraft.
In order to accurately simulate the energy distribution of a solar unmanned aerial vehicle and carry out related research, zhu Bingjie and the like research the relation between a photovoltaic cell and the attitude angle of the solar unmanned aerial vehicle, and by referring to the relation between a solar incident ray vector in an airship and an airship body coordinate system, an accurate solution of solar radiation can be obtained, but in the research, the efficiency of a photovoltaic module is assumed to be unchanged, and the relation of the efficiency of the photovoltaic module changing along with environmental conditions cannot be accurately reflected when the output and the input of an energy system are researched. Liu Li and the like introduce the energy flow of the solar/hydrogen aircraft in detail based on weight energy balance, power matching and energy management strategies, but the research only simulates the energy distribution condition during uniform-speed flight and cannot be directly applied to actual flight.
Adjusting the flight attitude is one of the methods to optimize the energy distribution. Wang Xiangyu proposes a multi-objective collaborative path planning algorithm for a solar unmanned aerial vehicle, which utilizes an improved ant colony algorithm to find an optimal path and optimize energy distribution, however, in this research, it is assumed that a photovoltaic cell always outputs at the maximum power, and any flight trajectory cannot be simulated and optimized. Ni et al used neural networks to control the thrust, angle of attack and roll changes to maximize energy, but this study assumed constant photovoltaic module efficiency.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a method for quickly evaluating the energy distribution of a solar aircraft based on GUI visualization, which can predict the energy distribution condition of the solar aircraft. In the method, the surface temperature of the photovoltaic cell is predicted by utilizing a heat transfer model of the surface of the wing, so that the temperature change of the surface of the photovoltaic cell is obtained; the method comprises the following steps of (1) researching the real-time state and the input and output conditions of each participating energy flow system by constructing a multi-system strong-coupling solar aircraft energy flow model; the flight trajectory of the aircraft is regulated and optimized by using a genetic algorithm and taking the thrust, the attack angle and the roll angle as independent variables, so that the energy distribution condition and the flight performance of the solar aircraft are improved.
The technical scheme of the invention is as follows:
the method for rapidly evaluating the energy distribution of the solar aircraft based on GUI visualization comprises the following steps:
step 1: determining key parameters of the solar aircraft and the system participating in energy flow of the solar aircraft, and constructing a multi-system strong-coupling solar aircraft energy flow model;
step 2: designing a space motion track of an initial solar aircraft, taking the thrust, the attack angle and the roll angle of the aircraft as key flight parameters, obtaining the motion characteristics including flight speed, acceleration and yaw angle parameters and the stress characteristics including lift force and resistance parameters under the characteristics of high aspect ratio and low Reynolds number, and obtaining the power required by the aircraft to maintain the flight attitude in the flight process by the product of the thrust and the speed;
and 3, step 3: performing energy distribution assessment of the solar aircraft based on the GUI visualization: taking key parameters of the system participating in energy flow in the step 1 and thrust, attack angle and roll angle of the aircraft as input, outputting current voltage parameters, charge state parameters, power parameters and efficiency parameter curves of each system participating in energy flow of the solar aircraft under a given working condition according to the relation of internal power consumption and energy of the aircraft, analyzing the energy-participating energy storage conditions of the photovoltaic cell and the storage battery according to the output parameter curves, and evaluating the energy distribution condition;
and 4, step 4: optimizing flight conditions and energy distribution:
the method comprises the steps of constraining the ranges of the thrust, the attack angle and the roll angle of the aircraft under different working conditions, generating initial flight working conditions with the thrust, the attack angle and the roll angle as independent variables by using the maximum optimization target of the maximum output energy of the photovoltaic cell and the charge state of the storage battery at the end of simulation as well as the charge state at the initial stage of simulation, and screening out a group of flight working conditions with the optimal charge state of the storage battery and the optimal input and output of the battery by using a genetic algorithm.
Further, in step 1, the system for the solar aircraft to participate in energy flow comprises a solar radiation system, a photovoltaic cell system, a storage battery system and a thrust system comprising a motor and a propeller.
Further, the key parameters comprise the overall parameters of the solar aircraft, solar radiation parameters, photovoltaic cell parameters, storage battery key parameters and propeller key parameters; wherein:
the overall parameters of the solar aircraft comprise the aspect ratio, the reference wing area and the takeoff weight parameter information of the solar aircraft;
the solar radiation parameters comprise flight height, flight longitude and latitude and flight time;
the photovoltaic cell parameters comprise parameter information of open-circuit voltage, short-circuit current, maximum power point voltage and maximum power point current and photovoltaic cell laying rate of the photovoltaic cell in a standard state;
the key parameters of the storage battery comprise the corresponding relation between the battery capacity, the state of charge and the open-circuit voltage and the internal resistance parameter information;
the key parameters of the propeller comprise parameters of lift coefficient, drag coefficient, installation angle and diameter of a propeller disc.
Further, the models comprise a solar irradiance model, a heat transfer model, a photovoltaic cell model, a storage battery model, a propeller model, an aircraft kinematics model and an aircraft dynamics model, and mathematical expressions of the models are as follows:
solar irradiance model:
wherein S is total Represents the total solar irradiance; s beam Representing direct irradiance; s. the diffuse Represents the scattered irradiance; s pv Represents the solar irradiance that the photovoltaic cell can actually receive; unit vector of solar incident light is n s (ii) a The unit vector of the normal line of the surface of the photovoltaic cell is n p ；n b ＝[0,0,1] T ；T e b A transformation matrix representing the transformation from the ground coordinate system to the body axis system, according to which there is a relation to the attitude angle of the aircraft:
wherein psi represents a yaw angle, theta represents a pitch angle, and phi represents a roll angle;
a heat transfer model:
wherein, q ″) rad,sun Represents the thermal radiation flux of the sun to the photovoltaic cell; q ″) rad,wing Representing the difference of the thermal radiation flux of the wing surface and the external environment; q ″) conv Representing the heat convection flux between the upper surface of the wing and the ambient atmosphere; q ″) elec Representing the electric energy flux generated by the photovoltaic cell in this process; rho pv Represents the areal density of the photovoltaic cell; (c) p ) pv Represents the specific heat capacity of the photovoltaic cell; t represents the wing surface temperature; t represents time;
photovoltaic cell model:
wherein, V pv And I pv The output voltage and the output current of the photovoltaic cell are respectively; i is sc ,V oc ,I m ,V m Short-circuit current, open-circuit voltage, maximum power point current and maximum power point voltage under any condition are respectively; under standard conditions, the short-circuit current when the circuit of the photovoltaic cell is short-circuited is I scref The open circuit voltage when the circuit is open is V ocref When the output power of the battery reaches the maximum value, the corresponding maximum power point current is I mref The maximum power point voltage at this time is V mref ；S pv Solar irradiance received by a photovoltaic cell in unit time and unit area is calculated according to parameters of longitude and latitude, time and height; s ref Represents a reference solar irradiance; Δ T is the difference between the actual temperature of the battery and the reference temperature of the battery, Δ T = T-T ref ；T ref Represents a battery reference temperature; Δ S = S-S ref The difference between the actual solar irradiance received by the cell and the reference solar irradiance; e is a natural logarithm base number; a, b and c are compensation coefficients;
a storage battery model:
wherein the ideal voltage source voltage V ocbat Represents the electromotive force of the battery; r is a radical of hydrogen 0 And r 1 Indicating the internal resistance of the storage battery; c 1 A capacitor connected in parallel with the resistor; i is bat Represents the total current flowing through the battery; v bat Representing the voltage of the load across the battery; c bata A charge representing a fully charged state of the battery; c bat0 Representing the electric quantity of the storage battery at the initial moment; SOC represents the state of charge of the battery, SOC 0 Represents the state of charge at the initial time; integral formula I bat dt is the integral over time of the current through the battery from the initial state to the assumed state;
propeller model:
where ρ represents the atmospheric density; c Lp Representing the lift coefficient of the propeller; t is a unit of p Representing propeller thrust; eta p Representing propeller efficiency; the angle between the local speed and the plane of rotation is phi p ；γ p Is a lift drag angle; s p Is the area of the propeller; v represents the aircraft flight speed;
an aircraft dynamics model:
wherein V represents the flying speed; t represents thrust; d represents flight resistance; l represents aircraft lift; w is the aircraft weight; alpha represents an attack angle and is an included angle between the speed direction and the axis of the aircraft; gamma denotes a climbing angle;
is the roll angle; Ψ is a yaw angle; pitch angle θ = α + γ; g represents the gravitational acceleration;
the aircraft kinematics model is as follows:
wherein x, y and h respectively represent the displacement of the aircraft relative to the initial time position under the ground coordinate system.
Further, in step 3, the energy management strategy during flight is as follows: the photovoltaic cell generates electric energy to provide energy for the whole aircraft, the storage battery is used for storing the electric energy when the capacity of the photovoltaic cell is sufficient, the storage battery is used for discharging to provide energy for the aircraft when the capacity of the photovoltaic cell is insufficient, and the state of charge of the storage battery is constantly evaluated to enable the storage battery to be always in the range of (0.1,1), so that the battery is ensured not to be overcharged or overdischarged; in the whole process, the thrust system and the airborne equipment are energy consumption systems.
Further, in step 3, the visualized input sub-interfaces of the GUI are respectively: an aircraft flight information interface, a position time information interface, a photovoltaic cell parameter interface, a storage battery parameter interface and a thrust system parameter interface:
inputting basic model parameters and flight condition parameters of an aircraft by an aircraft flight information interface; the position time information interface guides a user to input information of initial states such as longitude, latitude, height and the like of the aircraft in a simulated initial state; respectively inputting relevant parameters of the photovoltaic cell and the storage battery, including cell current and voltage and resistance parameters; inputting relevant parameters of a motor and a propeller by a thrust system interface, wherein the relevant parameters comprise motor efficiency parameters, lift resistance coefficients of the propeller, installation angles, propeller diameters and propeller number;
the output sub-interface output curves of the GUI visualization are respectively as follows: the solar radiation intensity curve with time, the wing surface temperature curve with time, the photovoltaic cell power, the storage battery power, the airborne equipment power and the flight demand power curve with time, the current and voltage curves of the photovoltaic cell and the storage battery with time, the photovoltaic cell efficiency, the storage battery efficiency and the propeller efficiency curve with time, the state of charge of the storage battery curve with time, the attack angle, the climbing angle, the pitch angle, the yaw angle and the roll angle of the aircraft curve with time, the thrust, the speed and the altitude of the aircraft curve with time, the transverse and longitudinal coordinates of the aircraft and the flight path of the aircraft in three-dimensional space.
Advantageous effects
The invention provides a method for quickly evaluating energy distribution of a solar aircraft based on GUI visualization, which adopts a solar aircraft energy component model under the actual complex working condition, a key flight parameter model and an energy management strategy when the flight working condition of the solar aircraft is considered, and quickly predicts and analyzes the energy distribution of the solar aircraft; the flight performance of the solar aircraft is effectively improved by utilizing a genetic algorithm. The method has stronger applicability, and is suitable for calculating and optimizing the energy distribution of the solar aircraft with any parameter and under different flight states in a three-dimensional space.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1: the design method schematic diagram for rapidly evaluating energy distribution of the solar aircraft based on GUI visualization
FIG. 2 is a schematic diagram: the invention relates to a multi-system strong coupling solar aircraft energy flow model
FIG. 3: initial solar aircraft spatial motion trajectory of the invention
FIG. 4: energy distribution of all systems of the invention
FIG. 5 is a schematic view of: GUI-based visualization energy distribution assessment system interface
FIG. 6: energy distribution and track optimization algorithm flow chart
FIG. 7: optimized solar aircraft space motion trail
FIG. 8: photovoltaic cell output curve before and after optimization
FIG. 9: optimized front and rear battery state of charge curves
Detailed Description
The following detailed description of embodiments of the invention is intended to be illustrative, and not to be construed as limiting the invention.
In the prior art, analysis on key components such as a photovoltaic module and the like is lacked, and the solar airplane energy distribution and optimization research under complex working conditions is insufficient. The invention combines the mathematical physical models of a photovoltaic cell, a storage battery and a propeller, utilizes an equivalent circuit and a heat transfer model to describe the energy distribution and power characteristics of the solar aircraft in detail, and combines the kinematics and a kinetic equation of the aircraft to calculate and evaluate the energy distribution of the solar aircraft under different working conditions. In order to find the optimal energy distribution, a flight path is optimized by adopting a genetic algorithm. In order to visually display the evaluation result, full-machine energy rapid evaluation software with friendly and visual interfaces is also constructed. A schematic diagram of a design method for rapid assessment of solar aircraft energy distribution based on GUI visualization is shown in fig. 1.
The method comprises the steps of firstly, determining key parameters of the solar aircraft and the system participating in energy flow of the solar aircraft, and constructing a multi-system strong coupling solar aircraft energy flow model. The constructed multi-system strong coupling solar aircraft energy flow model is shown in figure 2. In the multi-system strong coupling model shown in fig. 2, the influence of the solar irradiance and the direction, the aircraft attitude angle and the thermal effect on the efficiency and the output power of the photovoltaic cell is considered, the change situation of the state of charge and the power of the storage battery with time based on a first-order RC equivalent circuit model is considered, the change situation of the efficiency and the process ratio of the propeller model with time based on the phyllotactic theory is considered, the relation between the motion trajectory of the aircraft in a three-dimensional space and the thrust, the attack angle, the speed, the attitude angle and the lift resistance of the aircraft is considered, and the energy storage change of the capacity of the photovoltaic cell and the storage battery can be obtained based on energy conservation according to the output energy of the photovoltaic cell, the residual electric quantity of the storage battery and the energy consumed by the aircraft.
Systems in which solar aircraft participate in the flow of energy include solar radiation systems, photovoltaic cell systems, battery systems, and thrust systems including motors and propellers.
The overall parameters of the solar aircraft comprise the aspect ratio, the reference wing area and the takeoff weight parameter information of the solar aircraft;
the solar radiation parameters comprise flight height, flight longitude and latitude and flight time;
the photovoltaic cell parameters comprise parameter information of open-circuit voltage, short-circuit current, maximum power point voltage and maximum power point current and photovoltaic cell laying rate of the photovoltaic cell in a standard state;
the key parameters of the storage battery comprise the corresponding relation between the battery capacity, the charge state and the open-circuit voltage and the internal resistance parameter information;
the key parameters of the propeller comprise parameters of lift coefficient, drag coefficient, installation angle and diameter of a propeller disc.
In this embodiment, the aspect ratio of the solar aircraft is determined to be 22, and the reference wing area is determined to be 240m 2 The takeoff weight of the aircraft is 9960N; the flight height of the aircraft at the initial moment is 10km, the longitude and latitude of the initial flight are east longitude 40 degrees and north latitude 120 degrees, and the flight time at the initial moment is 3 months, 21 days and 00; the total open-circuit voltage of a photovoltaic cell on the solar aircraft is 440V, the short-circuit current is 116.4A, the maximum power point voltage is 360V and the maximum power point current is 103.2A under a standard state, and the laying rate of the photovoltaic cell on the surface of the wing is 0.88; the battery capacity of the storage battery is 500Ah, the initial state of charge is 0.65, and the total open-circuit voltage is 209V; the propeller blades adopt NACA 23012 airfoil profiles, lift coefficients and drag coefficients are obtained from an airfoil profile library, the installation angle is 20 degrees, and the diameter of a propeller disc is 2m.
In the modeling process, the input and the output of the system of the solar aircraft participating in the energy flow are respectively analyzed, the model of each system is respectively established, the model comprises a photovoltaic cell model which is obtained by utilizing coordinate transformation and a heat transfer law and combining an equivalent circuit model and is coupled with the attitude angle and the thermal effect of the aircraft, more accurate system model parameters are input, and the energy distribution condition of the solar aircraft is obtained by utilizing the real-time capacity condition of the photovoltaic cell and the residual electric quantity and the total capacity of the storage battery and outputting the capacity energy storage change of the photovoltaic cell and the storage battery according to the coupling relation between the systems participating in the energy flow and an energy conservation-based energy management strategy.
The model specifically involved comprises a solar irradiance model, a heat transfer model, a photovoltaic cell model, a storage battery model, a propeller model, an aircraft kinematics model and an aircraft dynamics model, and mathematical expressions of the models are as follows:
solar irradiance model:
wherein S is total Represents the total solar irradiance; s. the beam Representing direct irradiance; s diffuse Representing scattered radiationAn illuminance; s pv Represents the solar irradiance that the photovoltaic cell can actually receive; unit vector of solar incident light is n s (ii) a The unit vector of the surface normal of the photovoltaic cell is n p ；n b ＝[0,0,1] T ；T e b A transformation matrix representing the transformation from the ground coordinate system to the body axis system, according to which there is a relation to the attitude angle of the aircraft:
where Ψ denotes a yaw angle, θ denotes a pitch angle, and Φ denotes a roll angle.
A heat transfer model:
wherein, q ″) rad,sun Represents the thermal radiation flux of the sun to the photovoltaic cell; q rad,wing Representing the difference of the thermal radiation flux of the wing surface and the external environment; q ″) conv Representing the heat convection flux between the upper surface of the wing and the ambient atmosphere; q ″) elec Representing the electric energy flux generated by the photovoltaic cell in this process; rho pv Represents the areal density of the photovoltaic cell; (c) p ) pv Represents the specific heat capacity of the photovoltaic cell; t represents the wing surface temperature; t represents time.
Photovoltaic cell model:
wherein, V pv And I pv The output voltage and the output current of the photovoltaic cell are respectively; i is sc ,V oc ,I m ,V m Short-circuit current, open-circuit voltage, maximum power point current and maximum power point voltage under any condition are respectively; under standard conditions, the short-circuit current when the photovoltaic cell circuit is short-circuited is I scref And an open circuit voltage at the time of open circuit of the circuit isV ocref When the output power of the battery reaches the maximum value, the corresponding maximum power point current is I mref The maximum power point voltage at this time is V mref ；S pv Solar irradiance received by a photovoltaic cell in unit time and unit area is calculated according to parameters of longitude and latitude, time and height; s ref ＝1000W/m 2 Denotes the reference solar irradiance; Δ T is the difference between the actual temperature of the battery and the reference temperature of the battery, and Δ T = T-T ref . Reference temperature T of battery ref ＝298.15K；ΔS＝S-S ref The difference between the actual solar irradiance received by the cell and the reference solar irradiance; e is the natural logarithmic base number, e =2.71838; a, b and c are compensation coefficients, a =0.0025/K and b =0.0005W/m 2 ,c＝0.00288/K。
A storage battery model:
wherein the ideal voltage source voltage V ocbat Represents the electromotive force of the battery; r is 0 And r 1 Indicating the internal resistance of the storage battery; c 1 A capacitor connected in parallel with the resistor; i is bat Represents the total current flowing through the battery; v bat Representing the voltage of the load across the battery; c bata The electric quantity representing the fully charged state of the storage battery, namely the rated capacity, is represented by Ah; c bat0 Representing the electric quantity of the storage battery at the initial moment; SOC represents the state of charge of the battery, SOC 0 Represents the state of charge at the initial time; integral formula I bat dt is the integral over time of the current through the battery from the initial state to the present state.
Propeller model:
where ρ represents the atmospheric density; c Lp Representing the lift coefficient of the propeller; t is p Representing propeller thrust; eta p Representing propeller efficiency; when the ground speed is highThe angle between the angle phi and the plane of rotation p ；γ p Is a lift drag angle; s p Is the area of the propeller; v represents the aircraft flight speed.
An aircraft dynamics model:
wherein V represents the flying speed; t represents thrust; d represents flight resistance; l represents aircraft lift; w is the aircraft weight; alpha represents an attack angle and is an included angle between the speed direction and the axis of the aircraft; gamma denotes a climbing angle;
is the roll angle; psi is a yaw angle; pitch angle θ = α + γ; g represents the gravitational acceleration. The thrust, the attack angle and the roll angle are independent variables, and other parameters in the formula are obtained by substituting the three independent variables into a solution equation in a formula (7) by combining the initial speed, the acceleration, the attack angle, the attitude angle, the climb angle, the flying height and the flying position.
The aircraft kinematics model is as follows:
wherein x, y and h respectively represent the displacement of the aircraft relative to the initial time position under the ground coordinate system.
And secondly, designing a space motion track of the initial solar aircraft.
The method comprises the steps of taking the thrust, the attack angle and the roll angle of an aircraft as key flight parameters, obtaining the motion characteristics including flight speed, acceleration and yaw angle parameters and the stress characteristics including lift force and resistance parameters under the characteristics of high aspect ratio and low Reynolds number, and obtaining the power required by the aircraft to maintain the flight attitude in the flight process by the product of the thrust and the speed. The spatial motion trajectory of the initial solar aircraft is shown in fig. 3.
And thirdly, carrying out energy distribution evaluation of the solar aircraft based on GUI visualization.
The method comprises the steps of taking key parameters of a system participating in energy flow in the first step and the thrust, the attack angle and the roll angle of an aircraft as input, outputting current voltage parameters, charge state parameters, power parameters and efficiency parameter curves of each system participating in energy flow of the solar aircraft under a given working condition according to the relation of internal power consumption and energy of the aircraft, and analyzing the energy-participating energy storage conditions of a photovoltaic cell and a storage battery according to the output parameter curves so as to evaluate the energy distribution condition.
The energy management strategy in the flight process is as follows: the photovoltaic cell generates electric energy to provide energy for the whole aircraft, the storage battery is used for storing the electric energy when the capacity of the photovoltaic cell is sufficient, the storage battery is used for discharging to provide energy for the aircraft when the capacity of the photovoltaic cell is insufficient, and the state of charge of the storage battery is constantly evaluated to enable the storage battery to be always in a (0.1,1) interval, namely the storage battery is ensured not to be overcharged or overdischarged; in the whole process, the thrust system and the airborne equipment are energy consumption systems. The energy distribution of all systems is obtained by using the MATLAB tool and the above energy management strategy in combination with the power, current, voltage and efficiency parameters or state of charge parameters of each system involved in energy flow as shown in fig. 4.
Based on the energy distribution evaluation of the GUI visualization, the input parameters include, during the visualization: the method has the advantages that key parameters of an aircraft battery equivalent circuit, parameters of an aircraft aspect ratio, weight and wing reference area, and flight track parameters with thrust, an attack angle and a roll angle as independent variables can be simply, quickly and accurately analyzed for the whole-aircraft energy flow condition, and flight motion characteristics and surface temperature parameters under various complex working conditions and different parameter states, and the change conditions of power, efficiency parameters and electrical characteristic parameters of each key energy system in a specified time are predicted. The user can predict the energy distribution of the aircraft under different flight conditions by adjusting the input parameters in the program, so that the application range of the software is enlarged, and the adaptability of the software is improved. The software expresses all calculation results in a curve chart form, so that the expression of the state of the aircraft and the energy distribution state of the aircraft is more visual, and a user can conveniently analyze specific conditions.
An energy distribution evaluation system input and output window based on GUI visualization is shown in fig. 5. The input sub-interfaces are respectively: the system comprises an aircraft flight information interface, a position time information interface, a photovoltaic cell parameter interface, a storage battery parameter interface and a thrust system parameter interface.
The flight information interface of the airplane mainly inputs basic model parameters and flight working condition parameters of the aircraft, the position and time information interface guides a user to input information of initial states of the aircraft, such as longitude, latitude, height and the like, of a simulated initial state, the parameter interface of the photovoltaic cell and the storage battery respectively inputs related parameters of the cell, including cell current voltage and resistance parameters, and the parameter interface of the thrust system inputs related parameters of the motor and the propeller, including motor efficiency parameters, lift resistance coefficients of the propeller, installation angles, propeller diameters and propeller numbers. The output sub-interface output curves are respectively: the solar radiation intensity curve with time, the wing surface temperature curve with time, the photovoltaic cell power, the storage battery power, the airborne equipment power and the flight demand power curve with time, the current and voltage curves of the photovoltaic cell and the storage battery with time, the photovoltaic cell efficiency, the storage battery efficiency and the propeller efficiency curve with time, the state of charge of the storage battery curve with time, the attack angle, the climbing angle, the pitch angle, the yaw angle and the roll angle of the aircraft curve with time, the thrust, the speed and the altitude of the aircraft curve with time, the transverse and longitudinal coordinates of the aircraft and the flight path of the aircraft in three-dimensional space. Wherein the power versus time curve may reflect the flow of energy within the aircraft.
And fourthly, carrying out optimization of flight working conditions and energy distribution.
The flight process comprises low altitude hovering, climbing flight, high altitude flight and gliding, the ranges of the thrust, the attack angle and the roll angle of the aircraft under different working conditions are restrained, the charge state of the storage battery at the end of simulation is larger than or equal to the charge state at the initial time of simulation, the maximum energy output by the photovoltaic battery is an optimization target, the initial flight working condition with the thrust, the attack angle and the roll angle as independent variables is generated, and a group of flight working conditions with the optimal charge state of the storage battery and the optimal input and output of the battery are screened out by utilizing intersection, heredity and variation. The optimization process needs to set the population number and the maximum iteration number, and the calculation is stopped when the iteration is equal to the maximum iteration number or the optimized working condition is basically unchanged.
The optimization objective is expressed in mathematical expression as: max f 1 ＝SOC end -SOC 0 ＞0，max f 2 ＝∫P pm dt. Wherein, SOC end Indicating the state of charge, SOC, of the battery at the end of the simulation 0 Indicating the state of charge, P, of the battery at the time of the simulation pm Represents the maximum power that the battery can output, and t represents the time of the simulation. The solar aircraft high-altitude long-endurance performance is improved by utilizing the gravitational potential energy storage idea and a genetic algorithm based on two optimization targets, and an optimization result is output. Setting population number N po And the maximum number of iterations N it 。p c Indicates the cross probability, p m Representing the mutation probability of the real code vector. And (4) rapidly sorting non-dominance by judging the dominance level of individuals in the population, and screening out a reasonable new parent generation according to the crowding degree. New populations are generated through crossover and mutation operations and iterations continue until the optimization objective is met. The energy allocation and trajectory optimization algorithm flow chart is shown in fig. 6.
The total solar energy in one day on the unit area after optimization is 5.25 multiplied by 10 8 J/m 2 Compared with the product before optimization, the product is improved by 5 multiplied by 10 5 J/m 2 The solar energy which can be received by the photovoltaic cell is 2.78 multiplied by 10 7 J/m 2 Compared with the product before optimization, the product is improved by 1.2 multiplied by 10 5 J/m 2 (ii) a After optimization, the total maximum energy which can be output by the photovoltaic cell is 9.92 multiplied by 10 8 J, increased by 5.4X 10 compared with that before optimization 7 J; the actual output total energy of the photovoltaic cell is 7.53 multiplied by 10 8 J, increased by 4.8X 10 compared with that before optimization 7 J; the total discharge energy of the storage battery is 3.05 multiplied by 10 8 J, reduced by 2.8X 10 compared with that before optimization 7 J; the total charging energy of the storage battery is 3.17 multiplied by 10 8 J, increased by 1.4X 10 compared with that before optimization 6 J; total energy consumed by aircraft when hovering around 10kmIs 3.23X 10 8 J, reduced by 5.8X 10 compared with that before optimization 7 J; after optimization, the state of charge at 24. The optimized flight trajectory is shown in fig. 7, and the comparison of the photovoltaic cell output and the battery state of charge before and after optimization is shown in fig. 8 and 9, respectively.
The energy distribution optimization process divides the flight process into four working conditions of hovering flight at the height of 10km, climbing flight, hovering flight at the height of 15km and gliding according to a genetic algorithm, and the state of charge of the storage battery is set within a (0.1,1) interval at the moment. With the state of charge of the storage battery at 24 days p Screening out a group of optimal flight conditions of the charge state of the storage battery and the input and output of the storage battery, and the population number N by utilizing the intersection, heredity and variation under each initial flight condition p Set to 20, maximum number of iterations N it At 500, the calculation is stopped when the iteration is equal to the maximum number of iterations or the optimized operating conditions are substantially unchanged.
Although embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and not to be construed as limiting the present invention, and that those skilled in the art may make variations, modifications, substitutions and alterations within the scope of the present invention without departing from the spirit and scope of the present invention.
Claims (6)
1. A method for rapidly evaluating energy distribution of a solar aircraft based on GUI visualization is characterized by comprising the following steps: the method comprises the following steps:
step 1: determining key parameters of the solar aircraft and the system participating in the energy flow of the solar aircraft, and constructing a multi-system strong-coupling solar aircraft energy flow model;
step 2: designing a spatial motion track of an initial solar aircraft, taking aircraft thrust, attack angle and roll angle as key flight parameters, obtaining the motion characteristics including flight speed, acceleration and yaw angle parameters and the stress characteristics including lift force and resistance parameters under the characteristics of high aspect ratio and low Reynolds number, and obtaining the power required by the aircraft to maintain the flight attitude in the flight process by the product of the thrust and the speed;
and step 3: performing energy distribution assessment of the solar aircraft based on the GUI visualization: taking key parameters of the system participating in energy flow in the step 1 and thrust, attack angle and roll angle of the aircraft as input, outputting current voltage parameters, charge state parameters, power parameters and efficiency parameter curves of each system participating in energy flow of the solar aircraft under a given working condition according to the relation of internal power consumption and energy of the aircraft, analyzing the energy-participating and energy-storing conditions of the photovoltaic cell and the storage battery according to the output parameter curves, and evaluating the energy distribution condition;
and 4, step 4: optimizing flight conditions and energy distribution:
the method comprises the steps of constraining the ranges of the thrust, the attack angle and the roll angle of the aircraft under different working conditions, generating initial flight working conditions with the thrust, the attack angle and the roll angle as independent variables by using the maximum optimization target of the maximum output energy of the photovoltaic cell and the charge state of the storage battery at the end of simulation as well as the charge state at the initial stage of simulation, and screening out a group of flight working conditions with the optimal charge state of the storage battery and the optimal input and output of the battery by using a genetic algorithm.
2. The method for rapid assessment of solar aircraft energy distribution based on GUI visualization of claim 1, wherein: in step 1, the system for the solar aircraft to participate in energy flow comprises a solar radiation system, a photovoltaic cell system, a storage battery system and a thrust system comprising a motor and a propeller.
3. The method for rapid assessment of solar aircraft energy distribution based on GUI visualization of claim 1, wherein: the key parameters comprise the overall parameters of the solar aircraft, solar radiation parameters, photovoltaic cell parameters, storage battery key parameters and propeller key parameters; wherein:
the overall parameters of the solar aircraft comprise the aspect ratio, the reference wing area and the takeoff weight parameter information of the solar aircraft;
the solar radiation parameters comprise flight height, flight longitude and latitude and flight time;
the photovoltaic cell parameters comprise parameter information of open-circuit voltage, short-circuit current, maximum power point voltage and maximum power point current and photovoltaic cell laying rate of the photovoltaic cell in a standard state;
the key parameters of the storage battery comprise the corresponding relation between the battery capacity, the charge state and the open-circuit voltage and the internal resistance parameter information;
the key parameters of the propeller comprise parameters information of lift coefficient, resistance coefficient, installation angle and diameter of a propeller disk.
4. The method for rapid assessment of solar aircraft energy distribution based on GUI visualization of claim 3, wherein: the model comprises a solar irradiance model, a heat transfer model, a photovoltaic cell model, a storage battery model, a propeller model, an aircraft kinematics model and an aircraft dynamics model, and mathematical expressions of the models are as follows:
solar irradiance model:
wherein S is total Represents the total solar irradiance; s beam Representing direct irradiance; s diffuse Represents the scattered irradiance; s pv Represents the solar irradiance that the photovoltaic cell can actually receive; unit vector of solar incident light is n s (ii) a The unit vector of the surface normal of the photovoltaic cell is n p ；n b ＝[0,0,1] T ；T e b A transformation matrix representing the transformation from the ground coordinate system to the body axis system, according to which there is a relation to the attitude angle of the aircraft:
wherein psi represents yaw angle, theta represents pitch angle, phi represents roll angle;
a heat transfer model:
wherein, q ″) rad,sun Represents the thermal radiation flux of the sun to the photovoltaic cell; q ″) rad,wing Representing the difference of the thermal radiation flux of the wing surface and the external environment; q ″) conv Representing the heat convection flux between the upper surface of the wing and the ambient atmosphere; q ″) elec Representing the electric energy flux generated by the photovoltaic cell in this process; rho pv Represents the areal density of the photovoltaic cell; (c) p ) pv Represents the specific heat capacity of the photovoltaic cell; t represents the wing surface temperature; t represents time;
photovoltaic cell model:
wherein, V pv And I pv The output voltage and the output current of the photovoltaic cell are respectively; I.C. A sc ,V oc ,I m ,V m Short-circuit current, open-circuit voltage, maximum power point current and maximum power point voltage under any condition are respectively; under standard conditions, the short-circuit current when the circuit of the photovoltaic cell is short-circuited is I scref The open circuit voltage when the circuit is open is V ocref When the output power of the battery reaches the maximum value, the corresponding maximum power point current is I mref The maximum power point voltage at this time is V mref ；S pv The solar irradiance received by the photovoltaic cell in unit time and unit area is calculated according to the parameters of longitude and latitude, time and height; s ref Representing reference solar radiationAn illuminance; Δ T is the difference between the actual temperature of the battery and the reference temperature of the battery, and Δ T = T-T ref ；T ref Represents a battery reference temperature; Δ S = S-S ref The difference between the actual solar irradiance received by the cell and the reference solar irradiance; e is a natural logarithm base number; a, b and c are compensation coefficients;
a storage battery model:
wherein the ideal voltage source voltage V ocbat Represents the electromotive force of the battery; r is 0 And r 1 The internal resistance of the storage battery is represented; c 1 A capacitor connected in parallel with the resistor; I.C. A bat Represents the total current flowing through the battery; v bat Representing the voltage of the load across the battery; c bata A charge representing a fully charged state of the battery; c bat0 Representing the electric quantity of the storage battery at the initial moment; SOC represents the state of charge of the battery, SOC 0 Represents the state of charge at the initial time; integral formula I bat dt is the integral over time of the current through the battery from the initial state to the assumed state;
propeller model:
wherein ρ represents an atmospheric density; c Lp Representing a propeller lift coefficient; t is p Representing propeller thrust; eta p Representing propeller efficiency; the angle between the local speed and the plane of rotation is phi p ；γ p Is a lift drag angle; s p Is the area of the propeller; v represents the aircraft flight speed;
an aircraft dynamics model:
wherein V represents the flying speed; t represents thrust; d represents flight resistance; l represents aircraft lift; w is the aircraft weight; alpha represents an attack angle and is an included angle between the speed direction and the axis of the aircraft; gamma denotes a climbing angle;
is the roll angle; Ψ is a yaw angle; pitch angle θ = α + γ; g represents the acceleration of gravity;
an aircraft kinematics model:
wherein x, y and h respectively represent the displacement of the aircraft relative to the initial time position under the ground coordinate system.
5. The method for rapid assessment of solar aircraft energy distribution based on GUI visualization of claim 1, wherein: in step 3, the energy management strategy in the flight process is as follows: the photovoltaic cell generates electric energy to provide energy for the whole aircraft, the storage battery is used for storing the electric energy when the capacity of the photovoltaic cell is sufficient, the storage battery is used for discharging to provide energy for the aircraft when the capacity of the photovoltaic cell is insufficient, and the state of charge of the storage battery is constantly evaluated to enable the storage battery to be always in the range of (0.1,1), so that the battery is ensured not to be overcharged or overdischarged; in the whole process, the thrust system and the airborne equipment are energy consumption systems.
6. The method for rapid assessment of solar aircraft energy distribution based on GUI visualization of claim 1, wherein: in step 3, the visual input sub-interfaces of the GUI are respectively: an aircraft flight information interface, a position time information interface, a photovoltaic cell parameter interface, a storage battery parameter interface and a thrust system parameter interface:
inputting basic model parameters and flight condition parameters of an aircraft through an aircraft flight information interface; the position time information interface guides a user to input information of initial states of the aircraft, such as longitude, latitude, altitude and the like, wherein the initial states are simulated; respectively inputting relevant parameters of the photovoltaic cell and the storage battery, including cell current and voltage and resistance parameters; inputting relevant parameters of a motor and a propeller by a thrust system interface, wherein the relevant parameters comprise motor efficiency parameters, lift resistance coefficients of the propeller, installation angles, propeller diameters and propeller number;
the output sub-interface output curves of the GUI visualization are respectively as follows: the solar radiation intensity curve with time, the wing surface temperature curve with time, the photovoltaic cell power, the storage battery power, the airborne equipment power and the flight demand power curve with time, the current and voltage curves of the photovoltaic cell and the storage battery with time, the photovoltaic cell efficiency, the storage battery efficiency and the propeller efficiency curve with time, the state of charge of the storage battery curve with time, the attack angle, the climbing angle, the pitch angle, the yaw angle and the roll angle of the aircraft curve with time, the thrust, the speed and the altitude of the aircraft curve with time, the transverse and longitudinal coordinates of the aircraft and the flight path of the aircraft in three-dimensional space.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211345095.1A CN115906275B (en) | 2022-10-31 | 2022-10-31 | Method for rapidly evaluating energy distribution of solar aircraft based on GUI (graphical user interface) visualization |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211345095.1A CN115906275B (en) | 2022-10-31 | 2022-10-31 | Method for rapidly evaluating energy distribution of solar aircraft based on GUI (graphical user interface) visualization |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115906275A true CN115906275A (en) | 2023-04-04 |
| CN115906275B CN115906275B (en) | 2023-06-16 |
Family
ID=86482609
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211345095.1A Active CN115906275B (en) | 2022-10-31 | 2022-10-31 | Method for rapidly evaluating energy distribution of solar aircraft based on GUI (graphical user interface) visualization |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115906275B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104182560A (en) * | 2014-01-08 | 2014-12-03 | 中国商用飞机有限责任公司北京民用飞机技术研究中心 | Aircraft flutter prediction and analysis method and device |
| CN107272721A (en) * | 2017-07-11 | 2017-10-20 | 北京昶远科技有限公司 | A kind of solar energy unmanned aerial vehicle flight path planing method flown based on day-night cycle |
| CN109408987A (en) * | 2018-11-01 | 2019-03-01 | 西北工业大学 | A kind of three-dimensional high lift device parametric method for meeting Engineering constraint based on FFD method |
| CN109740878A (en) * | 2018-12-20 | 2019-05-10 | 北京航空航天大学 | A kind of solar powered aircraft continuation of the journey appraisal procedure based on net energy distribution map |
| US20220261012A1 (en) * | 2021-02-17 | 2022-08-18 | Northrop Grumman Systems Corporation | Systems and methods for flight path optimization |
-
2022
- 2022-10-31 CN CN202211345095.1A patent/CN115906275B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104182560A (en) * | 2014-01-08 | 2014-12-03 | 中国商用飞机有限责任公司北京民用飞机技术研究中心 | Aircraft flutter prediction and analysis method and device |
| CN107272721A (en) * | 2017-07-11 | 2017-10-20 | 北京昶远科技有限公司 | A kind of solar energy unmanned aerial vehicle flight path planing method flown based on day-night cycle |
| CN109408987A (en) * | 2018-11-01 | 2019-03-01 | 西北工业大学 | A kind of three-dimensional high lift device parametric method for meeting Engineering constraint based on FFD method |
| CN109740878A (en) * | 2018-12-20 | 2019-05-10 | 北京航空航天大学 | A kind of solar powered aircraft continuation of the journey appraisal procedure based on net energy distribution map |
| US20220261012A1 (en) * | 2021-02-17 | 2022-08-18 | Northrop Grumman Systems Corporation | Systems and methods for flight path optimization |
Non-Patent Citations (4)
| Title |
|---|
| MEHMET CEM CATALBAS 等: "A Novel Approach for Optimization of Nozzle Angle and Thrust Vectoring Controller via a Sub-Mutation Genetic Algorithm", 《INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING, INFORMATION & CONTROL: IJICIC》, vol. 13, no. 6, pages 1929 - 1940 * |
| 乔扬 等: "基于统计能量理论的飞行器壁板高频声振疲劳寿命预报及参数设计", 《工程力学》, vol. 36, no. 9, pages 230 - 236 * |
| 昌敏 等: "基于机翼-帆尾的高纬度跨年驻留太阳能飞机总体参数设计方法", 《航空学报》, vol. 35, no. 6, pages 1592 - 1603 * |
| 曹芸芸: "倾转旋翼飞行器飞行动力学数学建模方法研究", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》, no. 7, pages 031 - 5 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115906275B (en) | 2023-06-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Donateo et al. | A new approach to calculating endurance in electric flight and comparing fuel cells and batteries | |
| CN112060983B (en) | New energy unmanned aerial vehicle hybrid power supply architecture assessment method | |
| Hosseini et al. | Optimal path planning and power allocation for a long endurance solar-powered UAV | |
| Shaoqi et al. | Flight strategy optimization for high-altitude long-endurance solar-powered aircraft based on Gauss pseudo-spectral method | |
| Gao et al. | The equivalence of gravitational potential and rechargeable battery for high-altitude long-endurance solar-powered aircraft on energy storage | |
| CN108216679B (en) | Solar unmanned aerial vehicle overall parameter determination method and system | |
| Xi et al. | Energy-optimized trajectory planning for solar-powered aircraft in a wind field using reinforcement learning | |
| Zhang et al. | Nonlinear model predictive control-based optimal energy management for hybrid electric aircraft considering aerodynamics-propulsion coupling effects | |
| Wang et al. | Mission-oriented 3D path planning for high-altitude long-endurance solar-powered UAVs with optimal energy management | |
| Stroman et al. | The hybrid tiger: A long endurance solar/fuel cell/soaring unmanned aerial vehicle | |
| Clarke et al. | Evaluating the Performance and Acoustic Footprint of Aircraft for Regional and Urban Air Mobility | |
| CN114398721B (en) | Solar rotor unmanned aerial vehicle design method based on self-adjustment search pigeon crowd intelligence | |
| Mateja et al. | Towards energetic autonomy of UAV | |
| Liu et al. | Energy acquisition of a small solar UAV using dynamic soaring | |
| Salazar et al. | Optimization of the solar energy storage capacity for a monitoring UAV | |
| CN115906275B (en) | Method for rapidly evaluating energy distribution of solar aircraft based on GUI (graphical user interface) visualization | |
| Harasani et al. | Initial conceptual design and wing aerodynamic analysis of a solar power-based UAV | |
| CN117669908A (en) | Expressway comprehensive energy system optimization method, device, equipment and medium | |
| CN108022055A (en) | A kind of micro-capacitance sensor economic load dispatching method based on particle group model | |
| Karabetsky et al. | Conceptual design of solar rechargeable airplane | |
| Li et al. | Design of hybrid electric propulsion system for long endurance small UAV | |
| Shashati et al. | Design and Fabrication of a Solar Powered Unmanned Aerial Vehicle (UAV) | |
| Danjuma et al. | Design of power device sizing and integration for solar-powered aircraft application | |
| Papis et al. | Application of photovoltaic cells as a source of energy in unmanned aerial vehicle (UAV)–case study | |
| Karabetsky et al. | MULTI-OBJECTIVE OPTIMIZATION OF HYBRID ENERGY SYSTEM OF SOLAR RECHARGEABLE AIRCRAFT |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |