Endurance Unmanned Aerial Vehicle Research Articles

A control architecture to coordinate energy management with trajectory tracking control for fuel cell/battery hybrid unmanned aerial vehicles

Fuel cell/battery hybrid energy storage system (HESS) powered unmanned aerial vehicle (UAV) has the outstanding advantage of long endurance time. Trajectory tracking motion is a commonly used task execution mode of UAVs, especially in autonomous UAVs. This study aims at developing a control architecture to coordinate energy management with trajectory tracking control for fuel cell/battery hybrid UAVs. Its position tracking control adopts model predictive control (MPC) and an extended state observer to eliminate the modeling errors and effect of interference. The attitude tracking control adopts an auto-disturbance rejection controller having a quick response. The obtained control parameters are given as an input to the energy management block. Energy management strategies (EMSs) based on online dynamic programming and hierarchical MPC have been proposed. The results obtained from a simulation show that the proposed trajectory tracking control architecture can track the target trajectory stably with a small tracking error. The tracking performance is stable under interference. Experimental results show that dynamic programming is solved online with good control performance. Compared to ordinary EMSs, dynamic programming and hierarchical MPC can increase endurance time by 2.69% and 1.27%, respectively. The proposed control architecture verifies the coordination of energy management and trajectory tracking control, and prospected the advantages of the combination of fuel cell and autonomous driving for long endurance UAVs in the future.

Joint Energy and Performance Aware Relay Positioning in Flying Networks

Unmanned Aerial Vehicles (UAVs) have emerged as suitable platforms for transporting and positioning communications nodes on demand, including Wi-Fi Access Points and cellular Base Stations. This paved the way for the deployment of flying networks capable of temporarily providing wireless connectivity and reinforcing coverage and capacity of existing networks. Several solutions have been proposed for the positioning of UAVs acting as Flying Access Points (FAPs). Yet, the positioning of Flying Communications Relays (FCRs) in charge of forwarding the traffic to/from the Internet has not received equal attention. In addition, state of the art works are focused on optimizing both the flying network performance and the energy-efficiency from the communications point of view, leaving aside a relevant component: the energy spent for the UAV propulsion. We propose the Energy and Performance Aware relay Positioning (EPAP) algorithm. EPAP defines target performance-aware Signal-to-Noise Ratio (SNR) values for the wireless links established between the FCR UAV and the FAPs and, based on that, computes the trajectory to be completed by the FCR UAV so that the energy spent for the UAV propulsion is minimized. EPAP was evaluated in terms of both the flying network performance and the FCR UAV endurance, considering multiple networking scenarios. Simulation results show gains up to 25% in the FCR UAV endurance, while not compromising the Quality of Service offered by the flying network.

FLIGHT DYNAMICS AND STABLE CONTROL ANALYSES OF MULTI-BODY AIRCRAFT

Multi-body aircraft is a new concept aircraft consisting of multiple small unmanned aerial vehicles hinged-connected by wing tips. This concept aircraft can integrate the performance and advantages of two types of flying platforms: small unmanned aerial vehicles and high-altitude long endurance unmanned aerial vehicles. It has great development potential. Based on the Newton-Euler equation and on the lifting line method, it establishes a multi-body aircraft flight dynamics model, and analyzes the trim and stability characteristics of the multi-body aircraft system that allowing the relative degree of freedom of rolling motion with the dual-aircraft combination. The results show that, different from the traditional configuration aircraft, the multi-body aircraft system has an unstable relative motion flight mode, which is dominated by relative rolling motion. This configuration aircraft cannot fly stably in an uncontrolled situation. Based on the completion of the dynamics modeling, the Proportion-Integration-Differentiation control method is used for stable control. The stable control loop is designed separately for each single aircraft to achieve the purpose of stable flight. The simulation results show that the control method is effective and can quickly stabilize the divergent flight dynamics system.

Rotor flow-field timescale and unsteady effects on pulsed-flow turbocharger turbine

The turbocharged piston-driven engines are widely used in high altitude long endurance unmanned aerial vehicles (HALE UAVs). Repeated actions of engine pistons and valves give rise to engine pulsations resulting in intensive unsteady flow structures in the turbine rotor. The latter are, however, neglected in previous analytical studies leading to deviations in the prediction of turbine performance. The present work, for the first time, quantitatively investigates unsteady rotor flow-field timescale in a highly loaded mixed flow turbine using validated 3-D unsteady computational fluid dynamics (CFD) carried out by ANSYS-CFX. Results show that rotor flow-field timescale is in the same order as the rotation period of the rotor. In addition, the effects of rotor flow-field timescale on turbine performance are illustrated via an analogy of a pitching motion airfoil with the reduced frequency introduced as the criteria to measure the level of unsteadiness. With the increase of rotor unsteadiness, an evident inertial effect can be observed on the turbine power outputs. Rotor flow-field timescale should therefore be considered for improved turbine design and turbocharger-engine matching.

High altitude long endurance of unmanned aerial vehicle (UAV) ITB solar panel conceptual design

One of the factors for the long endurance of high altitude long endurance (HALE) of an unmanned aerial vehicle (UAV) that belong to Institut Teknologi Bandung, Indonesia or called as HALE UAV ITB is the design of battery and solar panel. This paper discusses the method to calculate battery and solar panel requirements for HALE UAV ITB to fly for more than 24 hours at 20.000 feet. Several designs, configuration, and type of solar panels are analysed to fulfil HALE UAV ITB requirements. The variable compared is solar panel area, weight, and types. As a result, the use of Monocrystalline Silicone solar cell was found to be much more efficient than Polycrystalline Silicon, CIGS Thin Film, and Amorphous Silicon Thin Film with power generated per area of 224 Watt/m2 and power per weight of 436 Watt/kg. The minimum area required for a Monocrystalline Silicone type solar cell to generate power is 5.94 m2 with a total cell weight of 5.31 kg.

Optimal Design of Outer-Rotor Surface Mounted Permanent Magnet Synchronous Motor for Cogging Torque Reduction Using Territory Particle Swarm Optimization

In this paper, territory particle swarm optimization (TPSO) is proposed for the optimal design of surface mounted permanent magnet synchronous motor (SPMSM) for high altitude long endurance (HALE) unmanned aerial vehicle (UAV). The proposed algorithm exploits the concept of a territory to the particle swarm optimization (PSO) to solve the problem that the conventional PSO cannot find the multimodal solutions. Also, by combining the stochastic method, PSO, with the deterministic method, pattern search method, it is possible to find optimal solutions quickly and accurately. The superiority of the proposed algorithm is verified through comparison in the test functions with niching genetic algorithm, which is well known multimodal optimization algorithm. The TPSO is applied to the optimization design of outer-rotor SPM for HALE UAV, and the optimal design with reduced cogging torque has been derived.

Joint Resource Allocation and 3D Aerial Trajectory Design for Video Streaming in UAV Communication Systems

Unmanned aerial vehicles (UAVs) can be flexibly deployed to offload cellular traffic or to provide video services for emergency scenarios without infrastructure. However, the inherent resource allocation and three-dimensional (3D) aerial trajectory design have not been formally studied. In this paper, we study the joint resource allocation and 3D aerial trajectory design for dynamic adaptive streaming over HTTP (DASH)-enabled services in a UAV communication system, where a UAV is employed as a base station for multiuser video streaming. Various factors are taken into account, including video data rate, quality variation, communication outage, play interruption, etc. By adopting a video streaming utility model, two fundamental problems are formulated with different practical aims: the first problem maximizes the minimum utility for all users within a given time horizon such that max-min fairness can be provided, and the second problem minimizes the UAV operation time subject to the individual utility requirement for all users to prolong UAV endurance. To tackle the first non-convex problem, we decouple it into three sub-problems, and a three-stage iterative algorithm is proposed to obtain a suboptimal solution by solving the three sub-problems with successive convex approximation and alternating optimization techniques. An exponential search based algorithm is proposed for the second problem by utilizing the structure of the considered problem and a similar three-stage iterative algorithm. Extensive simulations are carried out to evaluate the performance, and the results show that our proposed designs significantly outperform baseline schemes. Furthermore, our results reveal new insights of UAV movement for video streaming and unveil the tradeoff between utility and quality variance.

The multiple flying sidekicks traveling salesman problem with variable drone speeds

This research considers unmanned aerial vehicles (UAVs) that may travel at varying speeds in a last-mile delivery system involving a single truck and a fleet of UAVs. In existing truck-and-UAV delivery models that assume constant or unlimited UAV endurance, the natural conclusion is that operating UAVs at higher speeds will either decrease, or have no adverse effect on, total delivery times. However, in reality, UAV power consumption is a nonlinear function of both speed and parcel weight; flying at high speeds can dramatically reduce flight ranges, thus limiting the effectiveness of these logistics systems. This paper addresses the tradeoffs between speed and range in a new variant of the combined truck/UAV delivery problem in which UAV speeds are treated as decision variables. A three-phased algorithm is provided that dynamically adjusts UAV speeds to achieve superior performance, with the goal of minimizing the total delivery time (or makespan). Results indicate that significant time savings can be achieved by operating UAVs at variable speeds. Furthermore, under certain conditions, optimizing UAV speeds also results in shorter truck travel distances, reduced UAV energy consumption per trip, and less UAV loitering while waiting to rendezvous with the truck.

Fly Slower, Deliver Faster: the Multiple Flying Sidekicks Traveling Salesman Problem with Variable Drone Speeds

This research considers unmanned aerial vehicles (UAVs) that may travel at varying speeds in a last-mile delivery system involving a single truck and a fleet of UAVs. In existing truck-and-UAV delivery models that assume constant or unlimited UAV endurance, the natural conclusion is that operating UAVs at higher speeds will either decrease, or have no adverse effect on, total delivery times. However, in reality, UAV power consumption is a nonlinear function of both speed and parcel weight; flying at high speeds can dramatically reduce flight ranges, thus limiting the effectiveness of these logistics systems. This paper addresses the tradeoffs between speed and range in a new variant of the combined truck/UAV delivery problem in which UAV speeds are treated as decision variables. A three-phased algorithm is provided that dynamically adjusts UAV speeds to achieve superior performance, with the goal of minimizing the total delivery time (or makespan). Results indicate that significant time savings can be achieved by operating UAVs at variable speeds. Furthermore, under certain conditions, optimizing UAV speeds also results in shorter truck travel distances, reduced UAV energy consumption per trip, and less UAV loitering while waiting to rendezvous with the truck.

Design and Optimization of a High-altitude Long Endurance UAV Propeller

This paper presents a propeller designed for a solar unmanned aerial vehicle (UAV) at 22km altitude. The design objective for the 3-blade propeller is to achieve 72% efficiency and 7 N thrust, with 0.5588m diameter propeller rotating at 5500rpm under freestream velocity 50m/s. For such High-Altitude Long Endurance (HALE) flight vehicle, firstly, three low Reynolds number airfoils were assessed by airfoil aerodynamic performance analysis software Profili. As a result, FX 63-137 was selected for the best lift to drag ratio at given altitude. Secondly, a MATLAB program based on Joukowski propeller vortex theory was employed to determine three dimensional configuration of the blades. Then, CFD simulation was carried out on the preliminary design. Furthermore, optimal design method was employed to improve propeller efficiency of the preliminary design using software ISIGHT. Ten variables including chord lengths and blade pitch angles distribution at five spanwise sections were employed. Finally, the optimized propeller with power 467W was obtained, performance satisfying the requirement.

Energy acquisition of a small solar UAV using dynamic soaring

ABSTRACTDynamic soaring improves the endurance of Unmanned Aerial Vehicles (UAVs) by obtaining energy from the horizontal wind shear gradient. The use of dynamic soaring in small solar UAVs can mitigate the trade-off between energy capacity and battery weight to achieve continuous all-day flight. The goal of this study is to determine the optimal energy acquisition methods for small solar UAVs using dynamic soaring and to decrease the battery weight to achieve all-day flight. A dynamic soaring UAV model that considers the influence of the wind shear gradient and a solar power energy model are established. The conditions to obtain a closed-loop energy system during daytime and nighttime flights are discussed, and the minimum mass of the energy system required for these conditions is determined. Simulations of single-cycle circular flights and a 72-h continuous flight of a small solar UAV are performed. The analyses and simulation results show that: (1) the combination of dynamic soaring and solar technology significantly reduces the energy consumption and reduces the required battery weight, (2) the flight speed and flight attitude angles have significant effects on the optimal total energy acquisition and (3) wind fields with a large horizontal gradient and strong solar illumination provide energy and load advantages.

Energy-Efficient Data Uploading for Cellular-Connected UAV Systems

Integrating unmanned aerial vehicles (UAVs) into cellular networks offers a promising solution to support their efficient operations and achieve high-quality communication with the ground. In this paper, we consider a cellular-connected UAV communication system, in which one energy-constrained UAV flies from a given initial location to a final location while uploading data to the ground base stations (GBSs) along its flight. We study the joint design of UAV operation time, communication scheduling, as well as UAV trajectory and transmit power to maximize the data uploading throughput, subject to the communication quality of service (QoS) requirement and UAV energy budget constraints. We first consider an offline design approach by utilizing only the channel distribution information (CDI) that is available prior to the UAV's flight, which is formulated as a non-convex optimization problem and challenging to solve. By using path disretization and successive convex approximation (SCA) techniques, an efficient alternating optimization algorithm is proposed, which can converge to a solution that satisfies the Karush-Kuhn-Tucker (KKT) conditions. Then, we further study the online design approach by utilizing the instantaneous channel state information (CSI) that is available to the UAV in real time along its flight. As the online design problem has similar structure as that of the offline design, an adaptive online optimization algorithm is proposed. To further reduce the computational complexity, a low-complexity online algorithm based on receding horizon optimization (RHO) is developed by utilizing a combined offline and online design approach. Simulations are conducted to corroborate our study and the results demonstrate the performance gain of proposed designs as compared to various baseline schemes. Furthermore, our results unveil the tradeoff between system throughput and UAV endurance in the considered system.

An overview of methods for investigation of aeroelastic response on high aspect ratio fixed-winged aircraft

The thrust of increasing environmental and economic constraints on aircraft has enthused accelerated research in design of more economical and higher performance aircraft. Extensive experience in aerodynamic has established the use of high aspect ratio wings to improve the lift-to-drag ratio, a key parameter in determination of aircraft efficiency. Application of long slender wings has even more so intensified in the last decade due to emerging need for medium-to-high altitude long endurance (MALE/HALE) unmanned aerial vehicles (UAVs). However, such a wing comes at a trade-off of efficiency and safety. Longer wings tend of be more flexible and easily deform under load, hence are more vulnerable to the detrimental nature of aeroelastic effects. Divergence, control reversal and flutter are some major aeroelastic effects, which range from mere discomfort to complete destruction of body in flight. UAVs are most susceptible to this behaviour as their design incorporates very high aspect ratio wings. Numerous researches are available in literature which have focused on the explanation, calculation, and suppression of aeroelasticity; a subject which is as old as first heavier-than-air flight. This paper has attempted to cover the major aspect of aeroelasticity and summarize the state-of-the-art methods and approaches proposed by esteemed authors in this field for flutter prediction and suppression.

Improving the Performance of HALE UAV Communication Link Through MIMO Cooperative Relay Strategy

High-altitude long endurance unmanned aerial vehicles (HALE UAVs) are military and strategic UAVs that fly above the ground in the stratosphere. The ability of stealth technology and long flight time, has led to use of these UAVs for various military missions such as interception and spying, control guidance, remote sensing, navigation, surveillance and others. In this paper, improving the performance of HALE UAVs communication through multiple input multiple output (MIMO) cooperative relay with amplitude-and-forward strategy is investigated. In clear sky (without rain), two-hop system with line of sight (LoS) channels from source to relay and relay to destination is considered. In LoS-MIMO channels, due to correlation between the sub-channels, neither high-rank MIMO channel nor maximum capacity are achieved. However, based on antennas optimum placement that provide orthogonally between the received signals, maximum capacity will be obtained. The proposed scheme in this paper dramatically increases capacity relative to LoS-SISO channel and dual-hop MIMO Rayleigh up to 6 b/s/Hz and 2 b/s/Hz respectively. Also, simulation results verify exactness analytical expressions. However, rain as one of the most important ambient conditions causes the signal to be scattered in different directions. Therefore, LoS channel is changed to fading (Rayleigh) channel by increasing rainfall. In this case, telecommunication range is proposed as a meaningful metric, and outage probability (Poutage) based on telecommunication range for N-hop channel is extracted. In rainy conditions, simulation results show, the telecommunication range dramatically increases by increasing the number of relay UAVs for specified outage probability so that in the long-range, the outage probability decreases up to 50% with the increasing number of relays.

Self-Powered Solar Aerial Vehicles: Towards Infinite Endurance UAVs

A self-powered scheme is explored for achieving long-endurance operation, with the use of solar power and buoyancy lift. The end goal is the capability of “infinite” endurance while complying with the Unmanned Aerial Vehicle (UAV) dynamics and the required control performance, maneuvering, and duty cycles. Nondimensional power terms related to the UAV power demand and solar energy input are determined in a framework of Optimal Uncertainty Quantification (OUQ). OUQ takes uncertainties and incomplete information in the dynamics and control, available solar energy, and the electric power demand of a solar UAV model into account, and provides an optimal solution for achieving a self-sustained system in terms of energy. Self-powered trajectory tracking, speed and control are discussed. Aerial vehicles of this class can overcome the flight time limitations of current electric UAVs, thereby meeting the needs of many applications. This paper serves as a reference in providing a generalized approach in design of self-powered solar electric multi-rotor UAVs.

Design of hybrid electric heavy fuel MALE ISR UAV enabling technologies for military operations

PurposeThis paper aims to present the main results achieved in the frame of the TIVANO national-funded project which may anticipate, in a stepped approach, the evolution and the design of the enabling technologies needed for a hybrid/electric medium altitude long endurance (MALE) unmanned aerial vehicle (UAV) to perform persistent intelligence surveillance reconnaissance (ISR) military operations.Design/methodology/approachDifferent architectures of hybrid-propulsion system are analyzed pointing out their operating modes to select the more suitable architecture for the reference aircraft. The selected architecture is further analyzed together with its electric power plant branch focusing on electric system architecture and the selected electric machine. A final comparison between the hybrid and standard propulsion is given at aircraft level.FindingsThe use of hybrid propulsion may lead to a reduction of the total aircraft mass and an increase in safety level. However, this result comes together with a reduced performance in climb phase.Practical implicationsThis study can be used as a reference for similar studies and it provides a detailed description of propulsion operating modes, power management, electric system and machine architecture.Originality/valueThis study presents a novel application of hybrid propulsion focusing on a three tons class MALE UAV for ISR missions. It provides new operating modes of the propulsion system and a detailed electric architecture of its powertrain branch and machine. Some considerations on noise emissions and infra-red traceability of this propulsion, at aircraft level.

State of Charge Estimation Algorithm for Unmanned Aerial Vehicle Power-Type Lithium Battery Packs Based on the Extended Kalman Filter

The lack of endurance is an important reason restricting further development of unmanned aerial vehicles (UAVs). Accurately estimating the state of charge (SOC) of the Li-Po battery can maximize the battery energy utilization and improve the endurance of UAVs. In this paper, the main current methods for estimating the SOC of vehicles were explored and discussed to unveil their advantages and disadvantages. In addition, the extended Kalman filter algorithm based on an equivalent circuit model was used to estimate SOC of power-type Li-Po batteries at different temperatures. The result showed that the closed-loop control method can effectively improve the battery life of small-sized electric UAVs.

Development of Path Planning Tool for Unmanned System Considering Energy Consumption

Increasing the flight endurance of unmanned aerial vehicles (UAVs) has received attention recently. To solve this problem, two research topics have generally appeared: Shortest-path planning (SPP) and remaining-flying-range estimation. In this work, energy-efficient path planning by considering the distance between waypoint nodes, the minimum and maximum speed of the UAV, the weight of the UAV, and the angle between two intersecting edges is proposed. The performances of energy-efficient path planning (EEPP) and generic shortest-path planning are compared using extended-Kalman-filter-based state-of-charge and state-of-power estimation. Using this path-planning tool and considering energy consumption during flight operation, two different path plans can be obtained and compared in advance so that the operator can decide which path to choose by consulting a comparison chart. According to the experimental results, the EEPP algorithm results in 0.96% of improved SOC leftover and 11.03 ( W ) of lowered SOP compared to the SPP algorithm.

Research on Duration Estimation of Rotor UAV Based on Flight Condition-Energy Consumption Identification

The quad-rotor UAV (Unmanned aerial vehicle) has a wide application market for its simple structure, easy operation and strong adaptability. During the flight, the endurance of UAV is an important parameter for flight planning, and it is of great significance to master the endurance capability of UAV. The endurance of UAV is mainly decided by the remaining capacity of the battery and the future energy consumption which changes with flight conditions. In this paper, a Flight Condition-Energy Consumption Model is established by analysing a large number of flight data with machine learning method, and the effects of different regression algorithms are compared. The validity of the model is verified by the actual flight. The endurance of the aircraft can be estimated using this model with the given remaining capacity of the battery and the future flight tasks.

Multidisciplinary wing design of a light long endurance UAV

PurposeThe purpose of this paper is finding the optimal geometric parameters and developing of a method for optimizing a light unmanned aerial vehicle (UAV) wing, maximizing, at the same time, its endurance with the assumed parameters of aircraft mission.Design/methodology/approachThe research is based on the experience gained by the author’s contribution to the project of building medium-altitude, long-endurance class, light UAV called “Samonit”. The author was responsible for the structure design, wind tunnel tests and flight tests of the “Samonit” aircraft. Based on the experience, the author was able to develop an optimization process considering various disciplines involved in the whole aircraft design topics such as aerodynamics, flight mechanics, structural stiffness and weight, aircraft stability and maneuverability. The presented methodology has a multidisciplinary nature, as in the process of optimization both aerodynamic aspects and the influence of wing geometric parameters on the wing structure and weight and the aircraft payload were taken into account. The optimal wing configuration was obtained using the genetic algorithms.FindingsAs a result, a set of wing geometrical parameters has been obtained that allowed for achieving twice as long endurance as compared with the initial one.Practical implicationsUsing the methodology presented in the paper, an aircraft designer can easily find the optimum wing configuration of a designed aircraft, satisfying the mission requirements in a best way.Originality/valueAn original procedure has been developed, based on the actual design, wind tunnel tests and numerical calculations of “Samonit” aircraft, enabling the determination of optimum wing configuration for a small unmanned aircraft.