Electric UAV Research Articles

Critical review on integrated real-time energy management strategy and digital twin applied to hybrid electric UAVs

Critical review on integrated real-time energy management strategy and digital twin applied to hybrid electric UAVs

Optimal power management and sizing of a fuel cell electric UAV

Optimal power management and sizing of a fuel cell electric UAV

Adaptive hierarchical energy management strategy for fuel cell/battery hybrid electric UAVs

Energy management is crucial to realize efficient operation for hybrid electric UAVs. Adaptive hierarchical energy management strategy (AHEMS) is proposed to improve energy management efficiency for hybrid electric UAVs. AHEMS includes an optimization layer and a tracking layer. The former optimizes battery state of charge (SOC) reference trajectory and demand power by considering hybrid energy system characteristics, flight mission requirement and UAV model constraints. Sequential convex optimization method is proposed to solve battery SOC global reference trajectory. The latter realizes online power allocation by tracking the battery SOC reference trajectory through proposed model predictive control based on convex optimization. Meanwhile, fuzzy logic neural network is proposed to adaptively adjust prediction horizon for balancing the computational cost and optimality. AHEMS takes battery health management into account and prevents battery from over charging or over discharging. Numerical simulation results demonstrate that AHEMS can improve the energy management efficiency. Less hydrogen is consumed and battery is used more efficiently. Compared with nonlinear model predictive control (NMPC) and fuzzy logic state machine (FLSM), AHEMS saves 19.2% and 29.7% hydrogen fuel, respectively. Experimental results indicate that AHEMS is applicable for online energy management. It has good energy management effect. AHEMS is conducive to promoting the application of hybrid electric UAVs.

A coordinated optimization method of energy management and trajectory optimization for hybrid electric UAVs with PV/Fuel Cell/Battery

There are complex coupling relationships between flight motion and energy management for hybrid electric fixed wing UAVs with photovoltaic/fuel cell/battery. Aiming at realizing high-energy-efficiency long endurance autonomous flight, this paper proposes a coordinated optimization method of trajectory optimization and energy management for hybrid electric UAVs. Numerical simulation and experiment are carried out. Separated by surplus demand energy except that produced by PV, this method includes an optimal energy flight trajectory optimization layer and an energy management layer. For the former, fuzzy neural network sequential convex optimization (FNNSCP) is proposed to handle the flight trajectory optimization problem for maximizing utilization solar energy. For the latter, an online energy management strategy based on convex quadratic programming MPC (CQPMPC) is proposed to realize the power allocation. Numerical simulation results show that FNNSCP reduced 2% energy requirement compared with Radau pseudo-spectral method (RPM) from flight trajectory optimization level. From energy management level, CQPMPC saves hydrogen consumption by 3.1% and 16.3% compared with nonlinear model predictive control (NMPC) and fuzzy logic state machine (FLSM), respectively. In the experiment, less hydrogen fuel is consumed by proposed method by 5.2% and 15.6% compared with NMPC and FLSM, respectively. Experimental results show that the proposed method has better energy-saving performance and excellent real time performance. It indicates that optimizing flight trajectory and improving energy management efficiency can realize the high-energy-efficiency flight of hybrid electric UAVs. This method is conducive to promoting the application of hydrogen energy in the field of UAVs.

Design optimization and power management of a fuel cell-battery fixed-wing electric UAV

This study aims for endurance improvement and energy saving by addressing, on the one hand, the design optimization (DO) of a hybrid electric source (HES) consisting of a fuel cell (FC) and a battery, intended for a fixed-wing electric UAV (EUAV) and, on the other hand, the power management (PM) of the sources. The DO employed the particle swarm optimization (PSO) algorithm, which determines the FC power and the battery capacity that offer the sources the least weight; the findings resulted in a weight reduction of 8%; this gain saves a total energy of 90.28 kJ that can extend the “endurance stage” by more than 26 min. Three power management strategies (PMS) are examined: frequency separation (FS), which gives good performance in PM and protects the FC from dehydration by smoothing its response; power limitation (PL) which protects the FC from exceeding its maximum power, and fuzzy logic (FL), which allows for more flexible power distribution between the sources and has the main advantage of controlling the battery state of charge (SOC). A fourth strategy was developed by combining the benefits of these three strategies. This hybrid PMS (HPMS) saves 2% of FC energy compared to the FL strategy. FS and PL save, respectively, 41% and 44% of FC energy, but the SOC can drop significantly, especially for longer missions. The experimental findings, achieved using a laboratory test bench, validate the simulated results obtained from MATLAB/Simulink software, confirming the validity and performance of the proposed HPMS.

Modeling and Dynamic Stability Analysis of Distributed Electric Propulsion Tilt-Rotor UAV

Distributed electric propulsion tilt-rotor unmanned aerial vehicles (TRUAVs) with a lift-increasing flap in the propulsion wake have better aerodynamic efficiency than traditional tilt-rotor unmanned aerial vehicles and better takeoff/landing capacity than fixed-wing aircraft. However, for this configuration, establishing the propulsion–aerodynamic coupling model between the flap and the duct is difficult. This paper presents a flight dynamics model with propulsion–aerodynamic coupling components and analyzes dynamic characteristics during the transition period for TRUAVs with a distributed-propulsion/flap configuration. The development of the flight dynamics model considers the descriptions of the duct model, the lift-increasing flap model, and the propeller model. The model of the lift-increasing flap in both the duct exhaust jet and the freestream is the key component of the vehicle dynamics equations and is validated with experimental data and computational fluid dynamics results. Based on the dynamics model, the transition corridor of the tilt-rotor aircraft with multiple asynchronous tilting components and a geometrical constraint is calculated and analyzed. Additionally, the longitudinal dynamics stability of the aircraft in different flight speeds and configurations is assessed based on the numerical differentiation method. The results showed that the vehicle flight speed has more influence on longitudinal short-period stability than the angle of attack (AOA) of the flap. Also, the longitudinal long-period stability is affected by both the vehicle flight speed and the AOA of the flap. Finally, a mathematical derivation is developed to analyze the aircraft’s unstable state. The presented analysis results show that the stability of the long period is affected by the velocity derivative of the fuselage’s lift.

Preliminary weight estimation of canister based light foldable wing electric propulsion UAV, as a platform for swarm applications

Lots of disruptive UAV technologies are rising every day. Especially in the design process, under the prism of the upcoming swarm trend, a novelty touch to new foldable designs has started. In combination with electric propulsion systems, those platforms come in reality. Because of their size, the same design can be enlarged and reduced with minor changes at its subsystems. This simplifies the construction process and minimizes the costs. Due to their application range both, civilian and military platforms started to develop their own foldable UAVs, basically for swarm applications. In this study, the basic parameters of such a scalable design will be proposed. A literature survey will be presented, to determine the most common sizes of those platforms and the battery market availability. Afterwards, a mission profile will form the basis of the conceptual process for different dimensional UAVs. Two different methods about the weight estimation of the UAV will be examined. The goal of this multilateral examination is that; enable the designer to precede to an appropriate selection of subsystems of the UAVs, i.e., battery, autopilot and telemetry systems based on the weight estimation.

Path Planning of Electric VTOL UAV Considering Minimum Energy Consumption in Urban Areas

As a new mode of transportation in the future, electric vertical take-off and landing unmanned aerial vehicles (eVTOL UAV) can undertake the task of logistics distribution and carry people in urban areas. It is challenging to carry out research designed to plan the path of eVTOL UAVs which can have a safe and sustainable operation mode in urban areas. Therefore, this work proposes a method for planning an obstacle-free path for eVTOL UAVs in urban areas with the goal of minimizing energy consumption. It aims to improve the safety and sustainability of eVTOL UAV operations. Based on variations of air density with height, a more accurate formula for calculating battery energy consumption of eVTOL UAV is derived. It is used in the vertical takeoff and landing phase and horizontal flight phase, respectively. Considering the influence of buildings on eVTOL UAV operation, a path planning method applicable to complex urban environments is proposed. The safe nodes of eVTOL UAV flight are obtained by using Voronoi diagrams based on building locations. Then, the complete shortest and obstacle-free path is obtained by using a Dubins geometric path and Floyd algorithm. After obtaining the obstacle-free paths for all flight height zones, the battery energy consumption of the eVTOL UAV in each flight height zone is calculated. Then, the flight height with the minimum energy consumption is obtained. The simulation results show that the path length obtained by the proposed path planning method is shorter than that obtained by particle swarm optimization; the total battery energy consumption changes in the same pattern in the low-altitude areas and high-altitude areas; the difference between the maximum and minimum energy consumption in the small area enables the eVTOL UAV to cover about 350 m more, and about 420 m more in the large area. Therefore, in future high-frequency UAV mission flights, choosing the altitude with the lowest energy consumption can reduce UAV operator costs. It can also significantly increase UAV transport range and make UAVs operate more sustainably.

Double-layer fuzzy adaptive NMPC coordinated control method of energy management and trajectory tracking for hybrid electric fixed wing UAVs

The energy management and trajectory tracking control are crucial to realize long-endurance autonomous flight for hybrid electric UAVs. This study aims to comprehensively consider energy management and trajectory tracking for hybrid electric fixed wing UAVs with photovoltaic panel/fuel cell/battery. A double-layer fuzzy adaptive nonlinear model predictive control method (DFNMPC) is proposed. Separated by the surplus demand power, energy management and trajectory tracking problem are decoupled into the high-layer fuzzy adaptive nonlinear model predictive controll problem (H-FNMPC) and low-layer fuzzy adaptive nonlinear model predictive controll problem (L-FNMPC). H-FNMPC solves the trajectory tracking and navigation control probelm for the greatest benefit of solar energy. L-FNMPC solves the power allocation problem of hybrid energy system for minimum equivalent hydrogen consumption. A fuzzy adaptive prediction horizon adjustment method based on UAV maneuvering degree is proposed to effectively improve proposed method adaptability to different mission profiles. Analogously, a fuzzy adaptive equivalent hydrogen consumption factor adjustment method in L-FNMPC is proposed to ensure the flexible utilization of battery. In addition, an equivalent hydrogen flow rate calculation method based on the real-time current ratio is proposed for PV/FC/Battery hybrid energy system. Numerical simulation results including a spiral trajectory tracking and a quadrilateral trajectory tracking, demonstrate that DFNMPC can simultaneously handle energy management and trajectory tracking problem for hybrid electric UAVs. Compared to hierarchical fuzzy state machine strategy, DFNMPC can save 13.3% hydrogen for the spiral trajectory tracking, and 56.9% for the quadrilateral trajectory tracking. It indicates that the energy efficiency can be improved from both levels of energy management and flight motion. The proposed method prospected for exploring high-energy-efficiency autonomous flight of hybrid electric UAVs in the future.

Development of a novel supervisory controller on a parallel-hybrid powertrain for small unmanned aerial systems

PurposeA hybrid-electric unmanned aerial vehicle (HE-UAV) model has been developed to address the problem of low endurance of a small electric UAV. Electric-powered UAVs are not capable of achieving a high range and endurance due to the low energy density of its batteries. Alternatively, conventional UAVs (cUAVs) using fuel with an internal combustion engine (ICE) produces more noise and thermal signatures which is undesirable, especially if the air vehicle is required to patrol at low altitudes and remain undetected by ground patrols. This paper aims to investigate the impact of implementing hybrid propulsion technology to improve on the endurance of the UAV (based on a 13.6 kg UAV).Design/methodology/approachA HE-UAV model is developed to analyze the fuel consumption of the UAV for given mission profiles which were then compared to a cUAV. Although, this UAV size was used as reference case study, it can potentially be used to analyze the fuel consumption of any fixed wing UAV of similar take-off weight. The model was developed in a Matlab-Simulink environment using Simulink built-in functionalities, including all the subsystem of the hybrid powertrain. That is, the ICE, electric motor, battery, DC-DC converter, fuel system and propeller system as well as the aerodynamic system of the UAV. In addition, a ruled-based supervisory controlled strategy was implemented to characterize the split between the two propulsive components (ICE and electric motor) during the UAV mission. Finally, an electrification scheme was implemented to account for the hybridization of the UAV during certain stages of flight. The electrification scheme was then varied by changing the time duration of the UAV during certain stages of flight.FindingsBased on simulation, it was observed a HE-UAV could achieve a fuel saving of 33% compared to the cUAV. A validation study showed a predicted improved fuel consumption of 9.5% for the Aerosonde UAV.Originality/valueThe novelty of this work comes with the implementation of a rule-based supervisory controller to characterize the split between the two propulsive components during the UAV mission. Also, the model was created by considering steady flight during cruise, but not during the climb and descend segment of the mission.

Radically new solutions for reducing the energy use by future aircraft and their operations

Nowadays, new developments of future aircraft focus on the electric and electric – hybrid aircraft, while features, especially the specific energy and thermal instability of the available accumulator technology cause serious problems. This paper aims to define, discuss, and evaluate how the radically new, so-called out-of-the-box solutions may improve energy efficiency, and reduce the energy consumptions of future aircraft and their operations. This study introduces a novel methodology for (i) evaluation of the energy efficiency, (ii) estimation of the possible energy consumption reduction, (iii) estimation of the used energy reductions. The practical part shortly describes the radically new technologies and solutions that can be applied for reducing the energy consumption of (iv) aircraft development, and (v) aircraft operations, including the ground and terminal operations, as well as discuss some results of two radically new concepts, namely maglev assisted take-off and landing and hybrid-electric aircraft with unconventional structural solutions. Among the developed out-of-the-box solutions, the required energy can be reduced significantly by the “undercarriage-less configuration concept”, and “electric UAV supporter concept” up to 21% and 10% respectively. In addition to this, the fuel burn can be reduced by 15–20% by the “Cruiser-Feeder Concept”.

Design of autonomous navigation system for electric patrol Unmanned Aerial Vehicle Based on Beidou Positioning and satellite based enhancement

In order to reduce the deviation of automatic inspection of transmission tower UAV and improve the efficiency of inspection work, the design of autonomous navigation system of electric power inspection UAV Based on Beidou Positioning and satellite based enhancement is proposed. On the basis of Beidou Positioning and satellite based enhancement, the automatic inspection projector and automatic inspection navigator of transmission tower UAV are designed, and the hardware design of the system is completed. This paper analyzes the endurance of UAV, calculates the coordinates of the best shooting point of UAV, and completes the planning of automatic inspection path of transmission tower UAV according to the horizontal offset coordinates of UAV in the process of transmission tower inspection. Combined with the automatic inspection algorithm of transmission tower UAV, the system software design is completed to realize the automatic inspection of transmission tower UAV. The simulation results show that compared with the traditional inspection system, the deviation of the designed UAV automatic inspection system for transmission tower is significantly reduced.

Application of 5G in Electric Power Inspection UAV

At present, under the background of the social development of the increasing popularity of 5G technology, the automatic inspection of power lines through 5G UAV has become an inevitable demand for the development of smart grid. 5G has brought advanced technical advantages to the power inspection UAV, overcoming the difficulties in flight environment, data transmission and image analysis. The use of 5G UAV realizes the intelligent panoramic operation of power inspection and is an important means to ensure the reliable operation of power grid. However, due to the constraints of relevant factors, the use of 5G inspection UAV is both challenging and imperative in the future. This paper mainly introduces the basic meaning and advantages of 5G technology and UAV, compares and analyzes the differences between manual inspection, traditional UAV and 5G UAV in power inspection, discusses the technical advantages of 5G UAV, and combines with application cases to prospect the development prospect and trend of 5G UAV inspection.

Improving tail accuracy of the predicted cumulative distribution function of time of failure

Prognostic information is used to make decisions such as when to perform maintenance or - in time sensitive and safety critical applications - when to change operational settings. Where distributions about expected end of life (EOL) are available, these decisions are often based on risk-informed thresholds, for example a 2σ or 3σ criterion which considers the probability of making a bad decision at 5% or 0.3%, respectively, as tolerable. Sampling-based techniques such as Monte Carlo Sampling (MCS) and Latin Hypercube Sampling (LHS) can provide effective approaches to the propagation and analysis of uncertainty. Due to its efficient manner of stratifying across the range of each sampled variable, LHS requires less computational effort than MCS and is therefore more often used. However, since the focus is placed on accurately predicting the tails of the Cumulative Distribution Function (CDF) of Time of Failure (ToF) sampling-base techniques may not properly represent these areas. Although one might be tempted to use a brute force approach and simply increase the number of samples, some safety-critical applications may be computationally constrained. Such applications include electric UAV where the decision making process has to be fast in order to take action as soon as possible. This paper explores the ability of MCS and LHS to perform tail prediction with small sample sizes. The results show that LHS does not provide a significant advantage over MCS in terms of characterizing the tails of the CDF of the battery End of Discharge (EOD) prediction. Then, a methodology that combines MCS and Kernel Density Estimation (KDE) is investigated. The advantages of KDE in terms of reducing sample size while improving tail accuracy are demonstrated on battery end-of-discharge data.

A power transfer model-based method for lithium-ion battery discharge time prediction of electric rotatory-wing UAV

This paper develops a power transfer model-based method to estimate real-time state of energy (SOE) and predict end of discharge (EOD) time of rotatory-wing UAVs lithium batteries under dynamic operational conditions. A discrete-time state-space model of battery is first established to model the process of battery power consumption and establish a mapping of battery unobservable state of energy (SOE) to measurable parameters such as voltage and current. Then a power consumption model of UAV is established based on predetermined flight mission of UAV using aerodynamics and momentum theory, which estimates power consumption of UAV under different operational conditions. Its calculation results can be directly used in battery state-space model as its input, while its model parameters are simultaneously updated by online measurements of consumed power. Finally, a Particle Filter (PF) approach with Adam optimization algorithm is developed to estimate SOE and predict EOD time on-line, and better prediction results compared to conventional PF are achieved. Real experiments on UAV verify the effectiveness of the proposed method.

컨벡스 최적화 기법 기반 전기추진 수직이착륙 무인기의 추진 시스템 고장 대처를 위한 회전익 모드 믹서 설계

본 논문은 전기 추진 수직이착륙 무인기의 형상에 적합하도록 회전익 모드에서 추진시스템이 고장난 상황을 대처하기 위한 컨벡스 최적화 기법 기반의 믹서를 제시한다. 각 모터 및 프로펠러의 고장 영향성을 분석하기 위하여 컨벡스 함수 성질을 이용하여 가용 조종력 집합을 계산하였으며 이를 도시하는 방법을 기술하였다. 조종력 할당을 최적화 문제로 정의하고, 실시간으로 최적해를 구하기 위하여 컨벡스 함수로 문제를 재정의하였다. 컨벡스 최적화 솔버를 사용하여 수직 이착륙 비행 모드의 믹서를 구현하였으며 조종력 할당 기법들의 성능을 가용 조종력 범위 집합으로 비교하였다. 최종적으로 비선형 6자유도 시뮬레이션을 통하여 타기법(의사역행렬 기법, 재분배의사역행렬 기법)과 비교 분석하였다.

Synergy Effects in Electric and Hybrid Electric Aircraft

The interest in electric and hybrid electric power system has been increasing, in recent times, due to the benefits of this technology, such as high power-to-weight ratio, reliability, compactness, quietness, and, above all, elimination of local pollutant emissions. One of the key factors of these technologies is the possibility to exploit the synergy between powertrain, structure, and mission. This investigation addresses this topic by applying multi-objective optimization to two test cases — a fixed-wing, tail-sitter, Vertical Take-off and Landing Unmanned Aerial Vehicle (VTOL-UAV), and a Medium-Altitude Long-Endurance Unmanned Aerial Vehicle (MALE-UAV). Cruise time and payload weight were selected as goals for the first optimization problem, while fuel consumption and electric endurance were selected for the second one. The optimizations were performed with Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and S-Metric Selection Evolutionary Multiobjective Algorithm (SMS-EMOA), by taking several constraints into account. The VTOL-UAV optimization was performed, at different levels (structure only, power system only, structure and power system together). To better underline the synergic effect of electrification, the potential benefit of structural integration and multi-functionalization was also addressed. The optimization of the MALE-UAV was performed at two different levels (power system only, power system, and mission profile together), to explore the synergic effect of hybridization. Results showed that large improvements could be obtained, either in the first test case when, both, the powertrain design and the aircraft structure were considered, and in the optimization of the hybrid electric UAV, where the optimization of the aircraft flight path gave a strong contribution to the overall performances.

Minimization of the waiting time to start performing a radiation monitoring mission via a fleet of unmanned aerial vehicles in the new zone of responsibility

The analysis of possible applications of unmanned aerial vehicles for per-forming radiation monitoring missions was carried out. This paper proposes an approach to minimization of the waiting time to start performing a radiation mon-itoring mission via a fleet of unmanned aerial vehicles (hereafter UAVs) in the new zone of responsibility. The approach includes the following steps: distribu-tion of UAVs in the zones of responsibility and setting the time for performing a mission for each UAV; determination of the starting position location where UAVs battery can be replaced; defining the new zone of responsibility and time for performing a mission in the zone; construction of an algorithm for calculating parameters necessary for solving the optimization problem; formulation of the optimization problem and constraints. Parameters to be calculated: the UAV flight time from the current mission zone to: a) starting position; b) a new zone (with making the intermediate landing and without making one); a flight time from the new zone to the starting position; the UAV battery life required for per-forming the mission in the new zone; the waiting time to start performing the mis-sion in the new zone and the current battery life for the UAV at the start of its mission in the new zone for the following cases: a) the UAV reaches the new zone with making the intermediate landing, b) the UAV reaches the new zone without making one. An example of the proposed approach implementation for a fleet, con-sisting of five Ukrainian electric UAVs “Furiia” and performing missions in five zones of responsibility (one UAV performs a mission in one zone) within the Za-porizhzhia NPP thirty-kilometre radius zone is given. Six possible new zones are considered and the waiting time to start performing a mission in each of these zones is given. It has been get that UAV 5, UAV 4 and UAV 2 can be assigned to three zones, two zones and one zone, respectively. UAV 1 and UAV 2 can not be used in any new zone. Note that the UAV 5 can be used once without making the intermediate landing at the starting position for its battery replacement and twice with making the intermediate landing. Further studies should take into account the following cases: the fleet consists of various UAVs, two or more UAVs should be assigned to the new zone.

An Application of the ECMS Strategy to a Wankel Hybrid Electric UAV

In a previous work, the authors optimized the hybrid electric power system for a tactical Unmanned Aerial Vehicle including a Wankel engine as thermal converter and a permanent magnet electric motor powered by lithium batteries. Startingfrom this optimal configuration, we address here the topic of a refined optimization of the energy management strategy, i.e. the contribution of the battery to the required power in each segment of the flight. The Equivalent Consumption Minimization Strategy (ECMS) was chosen with the goal of minimizing fuel consumption while fully depleting the energy stored in the battery from the beginning to the end of each mission.

Design and implementation of low cost thrust benchmarking system (TBS) in application for small scale electric UAV propeller characterization

Thrust Benchmarking System (TBS), a low cost and easy to manufacture instrument for electric UAV propulsion system performance measurement is being proposed. With one of its uses for determining the static thrust of a propeller based on simple empirical characterization modeling. In this paper, characteristic modeling is performed on 3 APC-Electric propellers with different pitch and diameter dimensions. As a result, there are 2 constants K1 and K2 which can express similar propeller characteristics with different dimensions. It costs IDR 1.6 million and took two-and-a-half months of manufacture and assembly process.