Electric Vertical Takeoff Research Articles

A heuristic approach for scheduling advanced air mobility aircraft at vertiports

Recent progress in electric vertical take-off and landing (eVTOL) vehicles suggests that soon these vehicles could safely and efficiently transport people and cargo in urban areas. Therefore, advanced air mobility vehicles could become an alternative means of transport to overcome traffic congestion in cities in the upcoming years. There has been enormous interest from companies and governments in recent years in developing such technologies and enabling markets for new air transportation services. Despite the interest in the topic, little research has been done to address the aircraft scheduling problem in advanced air mobility take-off and landing areas (vertiports). The vertiports serve as the airports of eVTOL vehicles and could experience congestion problems similar to those of airports. This work proposes two optimization models for scheduling departing and landing aircraft at the vertiports’ common ground taxi routes (taxiways), gates, and touchdown and lift-off (TLOF) pads. The mathematical models include advanced air mobility features such as separation rules and blocking constraints. As scheduling objectives, the first model maximizes the vertiport throughput, and the second model minimizes the deviation from the expected take-off/landing time. In addition, as a solution methodology, we developed two heuristic algorithms that use scheduling rules to assign and sequence the aircraft to the vertiport components. Computational results show that the optimization models find optimal schedules for small-sized instances of up to 10 aircraft, while the heuristic algorithms provide good results in terms of solution quality and computational time for large instances.

Data-Driven Diffraction Loss Estimation for Future Intelligent Transportation Systems in 6G Networks

The advancement of 6G networks is driven by the need for customer-centric communication and network control, particularly in applications such as intelligent transport systems. These applications rely on outdoor communication in extremely high-frequency (EHF) bands, including millimeter wave (mmWave) frequencies exceeding 30 GHz. However, EHF signals face challenges such as higher attenuation, diffraction, and reflective losses caused by obstacles in outdoor environments. To overcome these challenges, 6G networks must focus on system designs that enhance propagation characteristics by predicting and mitigating diffraction, reflection, and scattering losses. Strategies such as proper handovers, antenna orientation, and link adaptation techniques based on losses can optimize the propagation environment. Among the network components, aerial networks, including unmanned aerial vehicles (UAVs) and electric vertical take-off and landing aircraft (eVTOL), are particularly susceptible to diffraction losses due to surrounding buildings in urban and suburban areas. Traditional statistical models for estimating the height of tall objects like buildings or trees are insufficient for accurately calculating diffraction losses due to the dynamic nature of user mobility, resulting in increased latency unsuitable for ultra-low latency applications. To address these challenges, this paper proposes a deep learning framework that utilizes easily accessible Google Street View imagery to estimate building heights and predict diffraction losses across various locations. The framework enables real-time decision-making to improve the propagation environment based on users’ locations. The proposed approach achieves high accuracy rates, with an accuracy of 39% for relative error below 2%, 83% for relative error below 4%, and 96% for both relative errors below 7% and 10%. Compared to traditional statistical methods, the proposed deep learning approach offers significant advantages in height prediction accuracy, demonstrating its efficacy in supporting the development of 6G networks. The ability to accurately estimate heights and map diffraction losses before network deployment enables proactive optimization and ensures real-time decision-making, enhancing the overall performance of 6G systems.

Wind Tunnel Testing and Analysis of a Rigid, Variable Speed Rotor for eVTOL Applications

Many electric vertical take-off and landing (eVTOL) aircraft intended for the urban air mobility (UAM) market are currently being designed with multirotor configurations using variable speed fixed-pitch, rigid rotors for lift. These types of rotors, which are similar in construction to general aviation airplane propellers, are simpler than helicopter rotors and have no moving parts in the rotating frame. This paper discusses wind-tunnel testing of a full-scale, UAM multirotor size, fixed-pitch, rigid rotor with a focus on vibratory blade loads and on the ability to predict these loads with comprehensive analysis. Test results show that vibratory loads are very high, with peak-to-peak magnitudes up to three times greater than the steady component. Correlation of test data to comprehensive analysis using geometrically exact composite beam structural elements and dynamic inflow wake modeling captures the trends in the steady and vibratory loads though it underpredicts the magnitudes; an expected result with the level of wake modeling fidelity used. The paper also discusses the physical sources of the observed vibratory loads and suggests potential options for mitigating their magnitude.

Joby Completes Submission of Stage Three Certification Plans to the FAA

On July 06, 2023, Joby Aviation, Inc., a company developing electric vertical take-off and landing (eVTOL) aircraft for commercial passenger service, announced it had submitted all of its Certification Plans to the Federal Aviation Administration (“FAA”), marking further progress toward completing the third of five stages required to certify its aircraft for commercial use.

Trajectory optimization for takeoff and landing phase of UAM considering energy and safety

This study performs trajectory optimization for takeoff and landing of urban air mobility (UAM) considering the energy efficiency and safety. The longitudinal model of single-seater electric vertical takeoff and landing (eVTOL) is used. In order to minimize the energy consumption, the battery state-of-charge, estimated by the coulomb counting method, is set as the objective function and the vortex ring state avoidance constraint is applied to secure the safety. The state variables are restricted in consideration of the passenger's ride quality and the takeoff and landing reference volume. The numerical optimization is conducted using direct collocation method, and the effects of the objective function and constraint are analyzed. In addition, a simulation applying a uniform wind environment is also performed to analyze the effect of the wind environment.

Characterization of Low-Latency Next-Generation eVTOL Communications: From Channel Modeling to Performance Evaluation

Next-generation wireless communication networks are expected to offer extremely high data rates supported by very low latency and radically new applications, which require a new wireless radio technology paradigm. However, it is crucial to assist the radio link over the fast varying and highly dynamic channel to satisfy the diverse requirements of next-generation wireless networks. Recently, communication via autonomous electric vertical takeoff and landing (eVTOL) has gained momentum, owing to its potential for cost-effective network deployment. It is considered one of the most promising technologies conceived to support smart radio terminals. However, to provide efficient and reliable communications between ground base stations and eVTOLs as well as between eVTOLs and other eVTOLs, realistic eVTOL channel models are indispensable. In this paper, we propose a nonstationary geometry-based stochastic channel model for eVTOL communication links. The proposed eVTOL channel model framework considers time-domain nonstationarity and arbitrary eVTOL trajectory and is sufficiently general to support versatile C bands. One of the critical challenges for eVTOL is the fast vertical takeoff and landing flight patterns affecting the regular propagation communication channel. Moreover, we present a new method for estimating the SNR over the non-stationary fast dynamic time-variant eVTOL channel by utilizing the sliding window adaptive filtering technique. Furthermore, we present an information–theoretic approach to characterize the end-to-end transmission delay over the eVTOL channel and prove that the optimal transmission scheme strongly depends upon the eVTOL link configuration. In addition, to analyze the occurrence of deep fade regions in eVTOL links, we analyze the outage probability, which is an important performance metric for wireless channels operating over dynamic fading channels, and make an important observation that the outage probability increases non-linearly with the eVTOL height. Furthermore, we consider the commercially available eVTOL specifications and data to validate the channel model and analyze the Doppler shift and latency for the exponential acceleration and exponential deceleration velocities profiles during the takeoff and landing operation. This paper provides a new and practical approach for the design, optimization, and performance evaluation of future eVTOL-assisted next-generation wireless communications.

Demand analysis in urban air mobility: A literature review

Urban air mobility (UAM) is a novel concept that is revolutionizing urban transportation. This transformation is largely due to the development of electric vertical take-off and landing (eVTOL) vehicles, which have made UAM a reality in the urban region. The success of this emerging mode of transportation is largely dependent on market demand. However, there is a lack of systematic reviews on demand analysis for UAM. To address this gap, we conducted a comprehensive review of the recently published literature on demand analysis for UAM. We firstly identified the demand for UAM in various types of on-demand applications, including passenger services, cargo services, and other services. Secondly, we discussed and identified the factors that influence the market demand in UAM, such as time, cost, distance, congestion, safety, privacy, and noise. Additionally, we examined the existing qualitative and quantitative methods for demand analysis in UAM. We found that the most common techniques include stated-preference surveys, discrete choice models, and clustering algorithms. We further discussed the role of market demand in the UAM life cycle, highlighting the potential impacts of demand on the development, implementation, and regulation of UAM systems. Finally, we concluded our review by highlighting several opportunities for future research related to demand analysis for UAM, and these include feasibility of air shuttle services, potential cargo applications, public acceptance, infrastructure placement, integration with existing transportation, and novel demand estimation methods, while addressing various aspects of UAM life cycle, including vehicle technology, infrastructure, airspace, and operation management.

Ammonia energy storage for hybrid electric aircraft

This work considers the development of a hybrid electric vertical takeoff and landing aircraft with an NH3 engine. An NH3 cracker with an external heat supply from the engine and a high-temperature catalytic reactor is needed to crack part of the NH3 in H2 and N2. The engine has two turbochargers in cascade, an intercooler, and an SCR catalyst with additional NH3 injection before the catalyst to control emissions. The H2 is used to ignite an NH3 mixture which may also be enriched with hydrogen to address particularly slow-burning points. The proposed learn burn engine which features direct injection and jet ignition of H2 may have power densities above 100 kW per liter and fuel conversion efficiencies approaching 50%. This engine can be further specialized to work on a narrow range of speeds and loads, ideally, one single point, to produce electricity on board the aircraft. The energy storage per unit mass of the complete system is expected to reduce vs. diesel but not dramatically. Importantly, it is much better than the storage of energy in a battery.

Monolithically-stacked thin-film solid-state batteries

The power capability of Li-ion batteries has become increasingly limiting for the electrification of transport on land and in the air. The specific power of Li-ion batteries is restricted to a few thousand W kg−1 due to the required cathode thickness of a few tens of micrometers. We present a design of monolithically-stacked thin-film cells that has the potential to increase the power ten-fold. We demonstrate an experimental proof-of-concept consisting of two monolithically stacked thin-film cells. Each cell consists of a silicon anode, a solid-oxide electrolyte, and a lithium cobalt oxide cathode. The battery can be cycled for more than 300 cycles between 6 and 8 V. Using a thermo-electric model, we predict that stacked thin-film batteries can achieve specific energies >250 Wh kg−1 at C-rates above 60, resulting in a specific power of tens of kW kg−1 needed for high-end applications such as drones, robots, and electric vertical take-off and landing aircrafts.

A battery dataset for electric vertical takeoff and landing aircraft

Electric vertical takeoff and landing aircraft have a unique duty cycle characterized by high discharge currents at the beginning and end of the mission (corresponding to takeoff and landing of the aircraft) and a moderate power requirement between them with no rest periods during the mission. Here, we generated a dataset of battery duty profiles for an electric vertical takeoff and landing aircraft using a cell typical for that application. The dataset features 22 cells, comprising a total of 21,392 charge and discharge cycles. 3 of the cells use the baseline cycle while each of the other cells vary either charge current, discharge power, discharge duration, ambient cooling conditions, or end of charge voltage. While it was designed to mimic the expected duty cycle of an electric aircraft, this dataset is relevant for training machine learning models on battery life, fitting physical or empirical models for battery performance and/or degradation, and countless other applications.

Life-cycle analysis of electric vertical take-off and landing vehicles

ABSTRACT One way to avoid ground congestion is to take to the sky, using vertical take-off and landing craft or ‘VTOL’. This study examines opportunities, costs, and energy impacts for an eVTOL (electric VTOL) system across the Austin, Texas region. Using different demand levels and VTOL sizes (4 and 8 seaters), we estimate average minimum costs of $24.84 per person-trip and $0.98 per person-kilometer using 4-seaters, which is less than current ride-hailing costs in U.S. cities. However, ride-hailing is door-to-door, while eVTOLs rely on stations, with non-negligible access and egress costs. We find 4-seaters offer higher energy and greenhouse gas (GHG) savings, based on the Texas power grid’s current feedstocks, with eVTOL GHG emissions similar to those of all-electric cars, in operation: about 70 grams per passenger-kilometer. But an eVTOL’s lifetime emissions are estimated to be twice those of electric cars (per passenger-kilometer traveled).

A rule-based energy management strategy for hybrid powered eVTOL

In recent years, as the levels of air pollution reach alarming degrees, new energy aerial vehicles like electric Vertical Take-Off and Landing (eVTOL) aircraft have become the development trend of the future aviation industry. This paper presents a rule-based energy management strategy (EMS) for an eVTOL. The Hybrid Power System (HPS) is composed of Proton Exchange Membrane Fuel Cells (PEMFC) as the main energy source and Lithium-ion batteries (Li-ion) as auxiliary one. The onboard sources deliver power to the DC bus through two DC-DC converters. The main objective is to optimally split the power demand between the different sources while respecting their limits and extending their lifetimes. The adopted control strategy is based on State Machine Control (SMC). It is described as a set of rules based on some predefined conditions and thresholds over the control variables. It is chosen due to its simplicity of implementation, its reliability, and a low computation time. The relevance of this strategy is evaluated and implemented on a set of simulations for an eVTOL mission corresponding to a search and rescue flight. Results on power distribution, fuel cell dynamics, and battery parameters are analysed. They confirm the effectiveness of the proposed strategy.

Adoption of the Urban Air Mobility System: Analysis of technical, legal and social aspects from a European perspective

As the demand for mobility and traffic in European urban areas continues to grow, innovative transportation solutions, particularly Urban Air Mobility (UAM), are gaining increasing prominence. UAM takes advantage of the third dimension to reduce ground traffic by integrating low-noise electric vertical take-off and landing vehicles (eVTOLs). Nonetheless, the successful implementation of UAM necessitates not only technological advancements but also the legal framework and social considerations to guarantee effective and safe operations. Holistic investigations of UAM are scarce, especially in the European context. Therefore, this study discusses the developments and challenges of UAM from technical, legal, and social perspectives and derives a set of UAM-tailored design drivers for the effective deployment of UAM in Europe. A comprehensive literature review is conducted on the state of the art of UAM technologies, regulations, and public attitudes. Various eVTOL configurations are compared, taking into account pertinent system factors such as energy efficiency and suitability for short- or long-duration missions. Besides, the cost-effectiveness of eVTOL configurations for a specific mission is evaluated through a cost-optimization analysis: the total cost is calculated to be around 2 € per payload-kilometer, which is approximately tenfold the current price for road transport. The regulatory activities of the European Union Aviation Safety Agency are discussed for the period 2017-2022, during which several systematic improvements to the regulations have been introduced. Typical factors for assessing the public acceptance of UAM are identified, and a survey is conducted across European medium-sized cities to gain insights into public opinion. The survey results indicate that 59\% of the respondents are moderately positive toward UAM deployment, representing a more cautious attitude compared to findings from studies conducted in metropolitan cities or countries. Furthermore, 56\% of respondents are willing to try out delivery services with aerial vehicles, while, 32\% would use air taxis. This is in contrast with studies conducted in metropolitan areas or at the country level. Based on the proposed holistic investigation of UAM, the set of design drivers can be identified to reduce uncertainty in UAM adoption and ensure a flawless deployment.

Sizing Approach with Flight Time Comparison of An Electric Multirotor Propulsion Chain with Batteries and Fuel Cells

The concept of electric vertical take-off and landing (E-VTOL) aerial vehicles is gaining more and more attention, thanks to their non-polluting operation and simple air traffic management. Indeed, around the world, there are currently more than 500 projects that concern the development and improvement of their performances. Development of sizing methods for rapid selection of the propulsion chain components remains an important task in this process. In this paper, an approach for sizing and selecting the propulsion chain components of an E-VTOL aerial vehicle is developed and validated. First, the optimal pair motor/propeller is selected using a global nonlinear optimization in order to maximize the specific efficiency of these components. Second, two energy storage technologies are considered and sized in order to assess their influence on the aerial vehicle flight time. Finally, based on this sizing process, the optimized propulsion chain gross take-off weight (GTOW) is evaluated, using regression methods based on propulsion chain supplier data.

Development of an urban air mobility vehicle family concept by system of systems aircraft design and assessment

The concept of urban air mobility promises a modern air taxi transport solution providing on-demand air mobility and hence time savings compared to congested terrestrial transportation in major cities and metropolitan areas. To make it a reality, vehicles, infrastructure, services, and operations must be developed simultaneously and cross-linked. These interconnections and interactions of the multitude of systems involved necessitate a system of systems approach, which is accounted for and implemented through agent-based simulations. Accordingly, the system of systems simulation framework is tuned to vehicle architecture as well as fleet design and assessment, thus allows to expand the aircraft design process by fleet operations and transport network perspectives. In this paper, the top level aircraft requirements of electric vertical take-off and landing vehicles are investigated by a fleet-centric approach. Herein, two disparate configurations, i.e. multirotor and tiltrotor, are modelled to depict representative wingless and winged configurations. The optimal design points are found and traded off by formulating different measures of effectiveness accounting for conversion of passenger requests, fleet energy consumption, and vehicle load factor. In summary, this study demonstrates the need for system of systems simulations to derive market-and operations-tailored vehicles and fleets. Furthermore, work on heterogeneous fleet compositions is required.

Lightweight Solid Oxide Cell Design for Ammonia-Fed SOFC Systems

A lightweight solid oxide fuel cell (SOFC) was developed by OxEon Energy that demonstrates the potential for increased specific power (kW/g) suitable for the requirements of electric Vertical Take-off and Landing (eVTOL) applications. Fuel flexibility was demonstrated in button cells and stacks using both legacy electrolyte-supported SOFC structure and the lightweight structure. Button cell and stack performance was nearly identical among hydrogen, ammonia, and reformed natural gas. Durability testing shows similarly stable performance in each fuel. A button cell test in ammonia at 800 °C using the lightweight cell structure measured area specific resistance (ASR) of 0.25 Ω-cm2 in H2/N2 and NH3 fuel feeds and showed a peak power density of 0.98 W/ cm2 in NH3 fuel. Short term hold at 0.7 V showed stable performance.

Advanced Air Mobility Operation and Infrastructure for Sustainable Connected eVTOL Vehicle

Advanced air mobility (AAM) is an emerging sector in aviation aiming to offer secure, efficient, and eco-friendly transportation utilizing electric vertical takeoff and landing (eVTOL) aircraft. These vehicles are designed for short-haul flights, transporting passengers and cargo between urban centers, suburbs, and remote areas. As the number of flights is expected to rise significantly in congested metropolitan areas, there is a need for a digital ecosystem to support the AAM platform. This ecosystem requires seamless integration of air traffic management systems, ground control systems, and communication networks, enabling effective communication between AAM vehicles and ground systems to ensure safe and efficient operations. Consequently, the aviation industry is seeking to develop a new aerospace framework that promotes shared aerospace practices, ensuring the safety, sustainability, and efficiency of air traffic operations. However, the lack of adequate wireless coverage in congested cities and disconnected rural communities poses challenges for large-scale AAM deployments. In the immediate recovery phase, incorporating AAM with new air-to-ground connectivity presents difficulties such as overwhelming the terrestrial network with data requests, maintaining link reliability, and managing handover occurrences. Furthermore, managing eVTOL traffic in urban areas with congested airspace necessitates high levels of connectivity to support air routing information for eVTOL vehicles. This paper introduces a novel concept addressing future flight challenges and proposes a framework for integrating operations, infrastructure, connectivity, and ecosystems in future air mobility. Specifically, it includes a performance analysis to illustrate the impact of extensive AAM vehicle mobility on ground base station network infrastructure in urban environments. This work aims to pave the way for future air mobility by introducing a new vision for backbone infrastructure that supports safe and sustainable aviation through advanced communication technology.

Fast Sizing Methodology and Assessment of Energy Storage Configuration on the Flight Time of a Multirotor Aerial Vehicle

Urban air mobility (UAM), defined as safe and efficient air traffic operations in a metropolitan area for manned aircraft and unmanned aircraft systems, is being researched and developed by industry, academia, and government. This kind of mobility offers an opportunity to construct a green and sustainable sub-sector, building upon the lessons learned over decades by aviation. Thanks to their non-polluting operation and simple air traffic management, electric vertical take-off and landing (eVTOL) aircraft technologies are currently being developed and experimented with for this purpose. However, to successfully complete the certification and commercialization stage, several challenges need to be overcome, particularly in terms of performance, such as flight time and endurance, and reliability. In this paper, a fast methodology for sizing and selecting the propulsion chain components of an eVTOL multirotor aerial vehicle was developed and validated on a reduced-scale prototype of an electric multirotor vehicle with a GTOW of 15 kg. This methodology is associated with a comparative study of energy storage system configurations, in order to assess their effect on the flight time of the aerial vehicle. First, the optimal pair motor/propeller was selected using a global nonlinear optimization in order to maximize the specific efficiency of these components. Second, five energy storage technologies were sized in order to evaluate their influence on the aerial vehicle flight time. Finally, based on this sizing process, the optimized propulsion chain gross take-off weight (GTOW) was evaluated for each energy storage configuration using regression-based methods based on propulsion chain supplier data.

Battery cycle life assessment for a lift+cruise electric vertical takeoff and landing transporter drone

Advanced Air Mobility (AAM) is a new future concept of air transportation to move people and cargo effectively and safely between places that are under or not served by different transportation modes. Transporter drone is one of the potential vehicles envisaged to fulfill this future AAM needs. One of the key challenges and crucial components in enabling successful transporter drone flight is the batteries used as they have limited usage cycle lifespan that affects the system airworthiness significantly. Hence to ensure continuous airworthiness of the platform, it is vital to know or predict the battery State of Health (SOH) and cycle life accurately. This paper describes a systematic approach on battery cycle life assessment through experimental battery usage cycle test for a lift+cruise transporter drone using realistic operating flight profile. Analysis on the battery cycle test data collected provides useful battery health and usage cycle lifespan information for system preventive and predictive maintenance in maintaining its airworthiness. Battery SOH estimation was done using linear predictive models with the collected battery cycle data while battery cycle life model was formulated using a double exponential parametric regression model. The battery cycle data collected is made publicly available for the community.

A new method to perform lithium-ion battery pack fault diagnostics – Part 3: Adaptation for fast charging

Electric Vertical Take-Off and Landing (eVTOL) aircraft are expected to become ubiquitous in the future Urban Air Mobility (UAM) landscape. Several eVTOL aircraft propelled using Lithium-ion batteries are under development. However, despite the early spotlight, the manufacturers need to ensure safe long-term operation of the vehicles including strict checks on battery-related hazards. On the other hand, fast charging of eVTOL batteries is crucial to enable multiple flights per day and justify the economics of UAM. This work is aimed at contextualising battery safety for eVTOL through the modification of a battery fault diagnosis algorithm for fast charging. The algorithm was developed in Parts 1 and 2 of the paper to use the charging cycle data for detecting disconnection faults but tested only for low charging currents. This paper adapts the algorithm for fast charging through a novel technique termed as Partial Incremental Capacity (PIC). The PIC method was developed using experiments at single cell and supercell level before integrating it into the algorithm. Finally, the fault detection ability of the adapted algorithm was validated using a real-life eVTOL battery module. Thus, the updated version of the algorithm facilitates fault diagnosis while charging fast, making it ideal for implementation in eVTOL.