Search

To analyze the impact of electrical system thermal management on cruise performance and the selection of performance parameters under different operating conditions for the tilt-wing eVTOL, a tilt-wing eVTOL cruise simulation model is established by using the aircraft cruising speed as the control variable, the cruising time and electrical energy consumption as the objective functions, based on the 2D dynamics, drag, energy consumption and electrical system thermal management calculation model of the aircraft. Set different weights according to actual flight conditions,and optimize the solution based on the specific characteristics of the model using an improved particle swarm optimization algorithm. Taking the typical tilt-wing eVTOL aircraft Vahana as an example, performance parameters are obtained and compared. The simulation results show that the model has good optimization effects on reducing aircraft cruising time and reducing electrical energy consumption under various weight combinations. Compared to the most energy-efficient flight conditions, the fastest arrival can save about 50% of time but also consume 120% more electricity. Compared to the compromise of considering both time and energy consumption, the fastest arrival saves 20% of time while consuming 28% more electricity. [ABSTRACT FROM AUTHOR]

The plate-fin heat exchanger was designed for the liquid cooling thermal management system of the hybrid electric propulsion system for an electric vertical take-off and landing (eVTOL) vehicle. The offset-strip fin design was applied, and the performance of the heat exchanger was evaluated, particularly with respect to the inclination of the airflow entering the heat exchanger. The estimated performance during the design phase matched well with the experimental results. The inclination of the heat exchanger had a minimal effect on thermal performance, with a slight increase in performance as the inclination increased. However, the pressure difference along the airflow was affected, likely increasing as the inclination increased. The sensitivity of various parameters on coolant temperature was also investigated. The air inlet temperature had a significant effect on coolant temperature, followed by the coolant flow rate. Therefore, when designing the thermal management system, careful consideration should be given to the ambient air temperature and coolant flow rate. [ABSTRACT FROM AUTHOR]

As the value and importance of urban air mobility (UAM) are being recognized, there is growing attention towards UAM. To ensure that urban air traffic can serve passengers to the greatest extent while ensuring safety and generating revenue, there is an urgent need for a transportation scheduling plan based on safety considerations. The region of Beijing–Tianjin–Hebei was selected as the case study in this research. A real-time demand transportation scheduling model for a single day was constructed, with the total service population and total cost as objective functions, and safety intervals, eVTOL performance, and passenger maximum waiting time as constraints. A Joint Optimization of Cost and Scheduling Particle Swarm Optimization (JOCS-PSO) algorithm was utilized to obtain the optimal solution. The optimal solution obtained in this study can serve 138,610,575 passengers during eVTOLs' entire lifecycle (15 years) with a total cost of CNY 368.57 hundred million, with the cost of CNY 265.9 per passenger. Although it is higher than the driving cost, it saves 1–1.5 h and thus has high cost effectiveness during rush hours. [ABSTRACT FROM AUTHOR]

Urban air mobility (UAM) is a revolutionary approach to transportation in densely populated cities. UAM involves using small, highly automated aircraft to transport passengers and goods at lower altitudes within urban and suburban areas, aiming to transform how people and parcels move within these environments. On average, UAM can reduce travel times by 30% to 40% for point-to-point journeys, with even greater reductions of 40% to 50% in major cities in the United States and China, compared to land transport. UAM includes advanced airborne transportation options like electric vertical takeoff and landing (eVTOL) aircraft and unmanned aerial vehicles (UAVs or drones). These technologies offer the potential to ease traffic congestion, decrease greenhouse gas emissions, and substantially cut travel times in urban areas. Studying the applications of eVTOLs and UAVs in parcel delivery and passenger transportation poses intricate challenges when examined through the lens of operations research (OR). By OR approaches, we mean mathematical programming, models, and solution methods addressing eVTOL- and UAV-aided parcel/people transportation problems. Despite the academic and practical importance, there is no review paper on eVTOL- and UAV-based optimization problems in the UAM sector. The present paper, applying a systematic literature review, develops a classification scheme for these problems, dividing them into routing and scheduling of eVTOLs and UAVs, infrastructure planning, safety and security, and the trade-off between efficiency and sustainability. The OR methodologies and the characteristics of the solution methods proposed for each problem are discussed. Finally, the study gaps and future research directions are presented alongside the concluding remarks.

Abstract In order to enhance the stability of the tilt transition process, a new configuration of Quad-Tiltrotor UAV was presented in this paper. Firstly, numerical simulation was used to calculate and analyze the aerodynamic interaction between the front rotor/fuselage/rear rotor during the transition state mode. The calculation model of the isolated rotor, front-rear rotor, front rotor-fuselage, and front rotor-rear rotor-fuselage combination states are established. Besides, the effects of pitch, roll, and yaw moment on the fuselage at different tilt angles are analyzed. It is concluded that the front rotor is the leading factor in the aerodynamic interference of the whole UAV in the different combination states. The research results can provide a reference for the optimization design of the overall layout, structure, and flight control strategy of the cross-shaped quad-tiltrotor UAV, and can also provide solutions for the logistics application of urban air traffic.

Urban air mobility (UAM) is a revolutionary approach to transportation in densely populated cities. UAM involves using small, highly automated aircraft to transport passengers and goods at lower altitudes within urban and suburban areas, aiming to transform how people and parcels move within these environments. On average, UAM can reduce travel times by 30% to 40% for point-to-point journeys, with even greater reductions of 40% to 50% in major cities in the United States and China, compared to land transport. UAM includes advanced airborne transportation options like electric vertical takeoff and landing (eVTOL) aircraft and unmanned aerial vehicles (UAVs or drones). These technologies offer the potential to ease traffic congestion, decrease greenhouse gas emissions, and substantially cut travel times in urban areas. Studying the applications of eVTOLs and UAVs in parcel delivery and passenger transportation poses intricate challenges when examined through the lens of operations research (OR). By OR approaches, we mean mathematical programming, models, and solution methods addressing eVTOL- and UAV-aided parcel/people transportation problems. Despite the academic and practical importance, there is no review paper on eVTOL- and UAV-based optimization problems in the UAM sector. The present paper, applying a systematic literature review, develops a classification scheme for these problems, dividing them into routing and scheduling of eVTOLs and UAVs, infrastructure planning, safety and security, and the trade-off between efficiency and sustainability. The OR methodologies and the characteristics of the solution methods proposed for each problem are discussed. Finally, the study gaps and future research directions are presented alongside the concluding remarks. [ABSTRACT FROM AUTHOR]

The development of robust and high‐performance battery systems is crucial for the advancement of Electric Vertical Takeoff and Landing (eVTOL) vehicles for urban air mobility. This study evaluates the performance of different lithium‐ion battery chemistries under Electric Vertical Takeoff and Landing (eVTOL) load profiles. The actual flight data coupled with physical models is used to create discharge profiles for testing on developed lithium‐ion cells for eVTOLs. The performance of a standard liquid electrolyte (1.2 M LiPF6 in EC:EMC), labeled Gen‐2, is benchmarked and compared with a fast‐charging electrolyte (1.2 M LiFSI in EC:EMC), labeled XFC. Cell analysis involves the use of various techniques, such as impedance spectroscopy, polarization curves, and capacity retention measurements. Capacity retention is stable for both systems over 500 cycles, but unique discharge capacity trends are observed for different mission segments. During the initial takeoff hover stages, Gen‐2 electrolytes experience substantial voltage fade, while XFC electrolytes maintain consistent behavior. In general, the Gen‐2 electrolyte demonstrated lower discharge overpotentials and higher decay during cycling compared to the XFC electrolyte. This work highlights the complexity of eVTOL battery behavior and provides insights into battery system design, contributing to the advancement of battery energy storage solutions for urban air mobility. [ABSTRACT FROM AUTHOR]

In order to enhance the stability of the tilt transition process, a new configuration of Quad-Tiltrotor UAV was presented in this paper. Firstly, numerical simulation was used to calculate and analyze the aerodynamic interaction between the front rotor/fuselage/rear rotor during the transition state mode. The calculation model of the isolated rotor, front-rear rotor, front rotor-fuselage, and front rotor-rear rotor-fuselage combination states are established. Besides, the effects of pitch, roll, and yaw moment on the fuselage at different tilt angles are analyzed. It is concluded that the front rotor is the leading factor in the aerodynamic interference of the whole UAV in the different combination states. The research results can provide a reference for the optimization design of the overall layout, structure, and flight control strategy of the cross-shaped quad-tiltrotor UAV, and can also provide solutions for the logistics application of urban air traffic. [ABSTRACT FROM AUTHOR]

The transportation of patients in emergency medical situations, particularly in rural areas, often faces significant challenges due to long travel distances and limited access to healthcare facilities. These challenges can result in critical delays in medical care, adversely affecting patient outcomes. Addressing this issue is essential for improving survival rates and health outcomes in underserved regions. This study explored the potential of advanced air mobility to enhance emergency medical services by reducing patient transport times through the strategic placement of vertiports. Using North Dakota as a case study, the research developed a GIS-based optimization workflow to identify optimal vertiport locations that maximize time savings. The study highlighted the benefits of strategic vertiport placement at existing airports and hospital heliports to minimize community disruption and leverage underutilized infrastructure. A key finding was that the optimized mixed-mode routes could reduce patient transport times by up to 21.8 min compared with drive-only routes, significantly impacting emergency response efficiency. Additionally, the study revealed that more than 45% of the populated areas experienced reduced ground travel times due to the integration of vertiports, highlighting the strategic importance of vertiport placement in optimizing emergency medical services. The research also demonstrated the replicability of the GIS-based optimization model for other regions, offering valuable insights for policymakers and stakeholders in enhancing EMS through advanced air mobility solutions. [ABSTRACT FROM AUTHOR]

Electric tilt-wing flying cars are an efficient, economical, and environmentally friendly solution to urban traffic congestion and travel efficiency issues. This article addresses the high energy consumption and obstacle interference during the takeoff phase of the tilt-wing eVTOL (electric Vertical Takeoff and Landing), proposing a trajectory planning method based on energy minimization and obstacle avoidance. Firstly, based on the dynamics analysis, the relationship between energy consumption, spatial trajectory, and obstacles is sorted out and the decision variables for the trajectory planning problem with obstacle avoidance are determined. Secondly, based on the power discretization during the takeoff phase, the energy minimization objective function is established and the constraints of performance limitations and spatial obstacles are derived. Thirdly, by integrating the optimization model with the SLSQP (Sequential Least Squares Quadratic Programming algorithm), the second-order sequential quadratic programming model and decision variable update equations are derived, establishing the solution process for the trajectory planning problem of the tilt-wing eVTOL takeoff with obstacle avoidance. Finally, the Airbus Vahana A3 is taken as an example to verify and validate the effectiveness, stability, and robustness of the model and optimization algorithm proposed. The validation results show that the OTPEM (obstacle avoidance trajectory planning methodology based on energy minimization) can effectively handle changes in the takeoff end state and exhibits good stability and robustness in different obstacle environments. It can provide a certain reference for the three-dimensional obstacle avoidance trajectory planning of Airbus Vahana A3 and other tilt-wing eVTOL trajectory planning problems. [ABSTRACT FROM AUTHOR]

The last decade has witnessed significant progress towards zero-emission electric aviation. Lithium-ion batteries are at the centre of this technological transformation. However, electric flight requires suitable considerations for safety concerns associated with Lithium-ion batteries. Fault diagnostic approaches aimed at validating the safety of batteries before every flight have emerged as an attractive prospect. In this pursuit, a three-paper series proposing a novel fault diagnosis algorithm is presented. The algorithm is capable of diagnosing faults in an aircraft battery using the data collected during charging and was previously validated for a particular cell type under steady charging conditions. In this paper, two extensional aspects of the algorithm are investigated: cell-to-cell transferability and disparate charging conditions. While crucial for practical implementation, these aspects were overlooked in previous literature. Through experiments conducted at module-level, it was revealed that the algorithm could diagnose faults for a different cell type with minimal preliminary cell-level characterisation, thus demonstrating its ease of transferability. Moreover, modifications introduced in the algorithm enabled it to perform fault diagnosis under unsteady charging conditions for an aerospace module despite significant internal temperature gradients. Thus, the successful working of the algorithm in the considered aspects, which are unprecedented in literature, prove its feasibility for real-life application.

The electric vertical take-off and landing (eVTOL) aircraft offers the advantages of vertical take-off and landing, environmental cleanliness, and automated control, making it a crucial component of future urban air traffic. As competition intensifies, demands for aircraft performance are escalating, including forward flight speed and payload capacity. The article presents a novel eVTOL design with propulsive wings and establishes methodologies for propulsive wing unsteady numerical simulation and wind tunnel experiments, analyzing its aerodynamic characteristics and lift enhancement mechanism. The results indicate that the cross-flow fan (CFF) provides unique airflow control capabilities, enabling the propulsive wing to achieve remarkably high lift coefficients (exceeding 7.6 in experiments) and propulsion coefficients (exceeding 7.1 in experiments) at extreme angles of attack (30°~40°) and low airspeeds. On the one hand, the CFF effectively controls boundary layer flow, delaying airflow separation at high angles of attack; on the other hand, the rotation of the CFF induces two eccentric vortices, generating vortex-induced lift and propulsion. The aerodynamic performance of the propulsive wing depends on the advance ratio and angle of attack. Typically, both lift and propulsion coefficients increase with the advance ratio, while lift and drag coefficients increase with the angle of attack. The propulsive wing shows significant advantages and prospects for eVTOL aircrafts in the low flight velocity range (0–30 m/s). [ABSTRACT FROM AUTHOR]

Electric vertical takeoff and landing (eVTOL) aircraft represent a crucial aviation technology to transform future transportation systems. The unique characteristics of eVTOL aircraft include reduced noise, low pollutant emission, efficient operating cost, and flexible maneuverability, which in the meantime pose critical challenges to advanced power retention techniques. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimizations, however, adopt high-fidelity simulation models in an iterative manner resulting in a computationally intensive mechanism. In this work, we implement a surrogate-enabled inverse mapping optimization architecture, i.e., directly predicting optimal designs from design requirements (including flight conditions and design constraints). A trained inverse mapping surrogate performs real-time optimal eVTOL takeoff trajectory predictions with no need for running optimizations; however, one training sample requires one design optimization in this inverse mapping setup. The excessive training cost of inverse mapping and the characteristics of optimal eVTOL takeoff trajectories necessitate the development of the regression generative adversarial network (regGAN) surrogate. We propose to further enhance regGAN predictive performance through the transfer learning (TL) technique, creating a scheme termed regGAN-TL. In particular, the proposed regGAN-TL scheme leverages the generative adversarial network (GAN) architecture consisting of a generator network and a discriminator network, with a combined loss of the mean squared error (MSE) and binary cross-entropy (BC) losses, for regression tasks. In this work, the generator employs design requirements as input and produces optimal takeoff trajectory profiles, while the discriminator differentiates the generated profiles and real optimal profiles in the training set. The combined loss facilitates the generator training in the dual aspects: the MSE loss targets minimum differences between generated profiles and training counterparts, while the BC loss drives the generated profiles to share analogous patterns with the training set. We demonstrated the utility of regGAN-TL on optimal takeoff trajectory designs for the Airbus A 3 Vahana and compared its performance against representative surrogates, including the multi-output Gaussian process, the conditional GAN, and the vanilla regGAN. Results showed that regGAN-TL reached the 99.5% generalization accuracy threshold with only 200 training samples while the best reference surrogate required 400 samples. The 50% reduction in training expense and reduced standard deviations of generalization accuracy achieved by regGAN-TL confirmed its outstanding predictive performance and broad engineering application potential. [ABSTRACT FROM AUTHOR]

Electric vertical takeoff and landing (eVTOL) vehicles possess high payload transportation capabilities and compact design features. The traditional method of increasing propeller size to cope with high payload is no longer applicable. Therefore, this study proposes the use of coaxial counter-rotating propellers as the lift system for eVTOL vehicles, consisting of two coaxially mounted, counter-rotating bi-blade propellers. However, if the lift of a single rotating propeller is linearly increased without considering the lift loss caused by the downwash airflow generated by the upper propeller and the torque effect of the lift system, it will significantly impact performance optimization and safety in the eVTOL vehicles design process. To address this issue, this study employed the Moving Reference Frame (MRF) method within Computational Fluid Dynamics (CFD) technology to simulate the lift system, conducting a detailed analysis of the impact of the upper propeller's downwash flow on the aerodynamic performance of the lower propeller. In addition, the aerodynamic performance indicators of coaxial counter-rotating propellers were quantitatively analyzed under different speed conditions. The results indicated significant lift losses within the coaxial contra-rotating propeller system, which were particularly notable in the lift loss of the lower propeller. Moreover, the total torque decreased by more than 93.8%, and the torque was not completely offset; there was still a small torsional effect in the coaxial counter-rotating propellers. The virtual testing method of this study not only saves a significant amount of time and money but also serves as a vital reference in the design process of eVTOL vehicles. [ABSTRACT FROM AUTHOR]

The relentless expansion of urban populations and the surge in e-commerce have increased the demand for rapid delivery services, leading to an increase in truck traffic that contributes to urban congestion, environmental pollution, and economic inefficiencies. The critical challenge this poses is not only in managing urban spaces efficiently but also in aligning with global sustainability goals. This study addresses the pressing need for innovative solutions to reduce reliance on truck transportation in congested urban areas without compromising the efficiency of freight delivery systems. This study contributes a novel approach that leverages electrified and autonomous aircraft (EAA) cargo shuttles to shift the bulk of air transportable freight from road to air, specifically targeting underutilized airports and establishing vertiports in remote locations. By applying data mining techniques to analyze freight flow data, this research identifies key commodity categories and metropolitan statistical areas (MSAs) where the implementation of EAA services could significantly mitigate truck-induced congestion. The findings reveal that targeting a select few commodities and MSAs can potentially decrease truck traffic, with electronics emerging as the dominant commodity category, and cities like Los Angeles and Chicago as prime candidates for initial EAA service deployment. Stakeholders in urban planning, transportation logistics, and environmental policy will find this study's insights beneficial. This work lays a foundation for future innovations in sustainable urban mobility and logistics. [ABSTRACT FROM AUTHOR]

In the current era, a new class of lightweight, silent, and all-electric aircraft that can take off and land vertically is about to transform mobility in major urban centers. Safer and quieter than helicopters, and operating in some cases without a pilot, they can supplement land mobility. Indeed, urban air mobility (UAM) has recently been a hot topic for debate and scientific research. However, it requires new types of service and technology and a novel business model. For a successful implementation, this paper provides the most insightful knowledge and actors, focusing on demand assessment through current research advancements in the area of urban air mobility. For that purpose, bibliometric analysis has been conducted, using a four-step methodology based on the search of the most frequently used keywords. The research work investigated the needs of the main stakeholders and illustrated how UAM can mitigate the pressure put on decision-makers regarding the mobility demand. The results show recent trends in scientific publications and citations, most cited articles, countries, and organizations that are more involved in this research subject, keyword co-co-occurrence analysis to identify and analyze current research areas and their associated barriers and challenges, using the VOSviewer software and WoS analytic feature. [ABSTRACT FROM AUTHOR]

In this research, we employed the multi-attribute method TOPSIS to evaluate and compare the parameters of 53 Vectored Thrust eVTOL aircraft. The analysis encompassed three separate TOPSIS computations, each of them utilizing distinct approach to evaluate the weight coefficients of the comparison criteria (criteria preference determined by one subjective and two objective methods). The three computations yield the results as a measure of the relative closeness to the positive ideal solutions for all alternatives, allowing for the ranking of the alternatives from the closest to the farthest. The final ranking was determined from the average values of the computation results. The analysis revealed that, across all computations, only five eVTOL aircraft achieved scores exceeding 0.5, while in the final ranking, seven eVTOLs had average scores greater than 0.5. Conversely, all remaining eVTOLs achieved scores closer to the negative ideal solution (lower than 0.5), with as many as 18 of them failing to attain an average result greater than 0.2. The results of the analysis offer a comprehensive overview of the observed eVTOL projects, indicating which ones stand out based on the specified criteria.

Lithium-ion batteries play a crucial role in present-day energy storage systems, necessitating the development of precise prediction models to improve their performance and ensure safety. The present study introduces a comprehensive methodology that encompasses the calibration, validation, and application of two separate Li-ion battery electrochemical models: the equivalent circuit model and the electrochemistry-based model. The calibration and validation of these models are based on experimental data conducted under various operating conditions, including charge/discharge rates, calendaring temperature, and Hybrid Pulse Power Characterization (HPPC) tests. After the successful validation process, these models are used to generate synthetic data tailored to real-world applications, particularly electric vertical takeoff and landing vehicles (eVTOL). The primary objective is to assess the precision of battery performance prediction, wherein the synthetic data is thoroughly compared with real experimental data. The results demonstrate the effectiveness of the proposed approach in developing a model that reduces dependence on labor-intensive testing and associated equipment costs, reduces time for experimentation, and accelerates controller development for batteries. This work highlights the importance of precise predictive models in lithium-ion batteries, facilitating the effective investigation of practical applications and advancements in energy storage technology.

As the value and importance of urban air mobility (UAM) are being recognized, there is growing attention towards UAM. To ensure that urban air traffic can serve passengers to the greatest extent while ensuring safety and generating revenue, there is an urgent need for a transportation scheduling plan based on safety considerations. The region of Beijing–Tianjin–Hebei was selected as the case study in this research. A real-time demand transportation scheduling model for a single day was constructed, with the total service population and total cost as objective functions, and safety intervals, eVTOL performance, and passenger maximum waiting time as constraints. A Joint Optimization of Cost and Scheduling Particle Swarm Optimization (JOCS-PSO) algorithm was utilized to obtain the optimal solution. The optimal solution obtained in this study can serve 138,610,575 passengers during eVTOLs’ entire lifecycle (15 years) with a total cost of CNY 368.57 hundred million, with the cost of CNY 265.9 per passenger. Although it is higher than the driving cost, it saves 1–1.5 h and thus has high cost effectiveness during rush hours.

The plate-fin heat exchanger was designed for the liquid cooling thermal management system of the hybrid electric propulsion system for an electric vertical take-off and landing (eVTOL) vehicle. The offset-strip fin design was applied, and the performance of the heat exchanger was evaluated, particularly with respect to the inclination of the airflow entering the heat exchanger. The estimated performance during the design phase matched well with the experimental results. The inclination of the heat exchanger had a minimal effect on thermal performance, with a slight increase in performance as the inclination increased. However, the pressure difference along the airflow was affected, likely increasing as the inclination increased. The sensitivity of various parameters on coolant temperature was also investigated. The air inlet temperature had a significant effect on coolant temperature, followed by the coolant flow rate. Therefore, when designing the thermal management system, careful consideration should be given to the ambient air temperature and coolant flow rate.

Introducing Advanced Air Mobility (AAM) as a novel transportation mode poses unique challenges due to limited practical and empirical data. One of these challenges involves accurately estimating future passenger demand and the required number of air taxis, given uncertainties in modal shift dynamics, induced traffic patterns, and long-term price elasticity. In our study, we use mobility data obtained from a Dresden traffic survey and modal shift rates to estimate the demand for AAM air taxi operations for this regional use case. We organize these operations into an air taxi rotation schedule using a Mixed Integer Linear Programming (MILP) optimization model and set a tolerance for slight deviations from the requested arrival times for higher productivity. The resulting schedule aids in determining the AAM fleet size while accounting for flight performance, energy consumption, and battery charging requirements tailored to three distinct types of air taxi fleets. According to our case study, the methodology produces feasible and high-quality air taxi flight rotations within an efficient computational time of 1.5 h. The approach provides extensive insights into air taxi utilization, charging durations at various locations, and assists in fleet planning that adapts to varying, potentially uncertain, traffic demands. Our findings reveal an average productivity of 12 trips per day per air taxi, covering distances from 13 to 99 km. These outcomes contribute to a sustainable, business-focused implementation of AAM while highlighting the interaction between operational parameters and overall system performance and contributing to vertiport capacity considerations. [ABSTRACT FROM AUTHOR]

The direction of propeller rotation in a distributed electric-powered vertical take-off and landing (eVTOL) aircraft significantly influences control forces and induced drag during both helicopter and fixed-wing modes. This study proposes a strategy to determine the most effective rotational direction for each propeller. This approach effectively mitigates one-engine-inoperative (OEI) conditions during helicopter mode for a subscale eVTOL referred to as the optionally piloted personal air vehicle (OPPAV). Moreover, the study developed an optimal control law using the linear programming method, which minimizes the maximum power required for individual motors under OEI conditions. The lowest maximum power was achieved under OEI conditions when both the front and rear propellers in each pod rotated in the same direction. Furthermore, to validate this proposed control law, a tethered hover test was performed using the subscale OPPAV under OEI conditions. Our findings demonstrate that determining the rotational direction of propellers using the newly proposed reconfiguration control method significantly enhances the safety of eVTOL aircraft operating under OEI conditions. [ABSTRACT FROM AUTHOR]

The use of non-piloted eVTOL aircraft in non-segregated airspace requires reliable and deterministic automatic flight guidance systems for the aircraft to remain predictable to all the users of the airspace and maintain a high level of safety. In this paper we present a 3D trajectory generation module based on clothoid transition segments in the horizontal plane and high order polynomial transition segments in the vertical plane. The expressions of the coefficients of the polynomial are derived offline are used to generate the trajectory online, making the system capable of running in real time without requiring enormous computational power. For the horizontal plane, we focus on the flyby transition, and therefore present a thorough analysis of the flyby geometry and the limitations linked to this geometry and the construct of three-segment trajectory generation around a fixed turn rate. We present feasible solutions for these limitations, and show simulation results for the combined horizontal and vertical plane concepts, allowing the system to generate complex 3D trajectories. [ABSTRACT FROM AUTHOR]

This paper presents a mission data-handling algorithm that provides a data link interface between a flight control computer (FCC) and a ground control station (GCS) using the protocol standard STANAG 4586, AEP-84 Volume II. A subset of defined messages is used for the transmission of mission and area definition data. Functions for decoding uplink messages, processing received data, and encoding downlink messages are developed. Due to a modular software architecture, these functions can be used both for the onboard FCC, as well as for the GCS using additional logic, to invert the transmission direction. Furthermore, high level consistency and validation checks are performed on the transmitted data before forwarding the mission to the flight guidance functions. Successful transmission of mission and area data between the FCC and the GCS is performed using a high-fidelity model-in-the-loop simulation of a demo mission for a medical evacuation eVTOL aircraft. [ABSTRACT FROM AUTHOR]

With the continuous opening of low-altitude airspace and the development of aircraft such as electric vertical takeoff and landing (eVTOL) vehicles, urban air traffic has become a sustainable and green development direction for future transportation. Air route networks, as a mainstream design scheme for air traffic, are able to provide prerequisites for eVTOL and other green aircraft to enter urban airspace for safe operation, among which air route planning is a fundamental component of air route network design. Currently, most of the research on aircraft path planning is performed in free airspace, lacking the analysis and processing for the complex operation environment, which has led to the high risk and large operation cost of path planning results, failing to meet the demand for safe and efficient development in the future. Aiming at the above problems, eVTOL-oriented air route planning research was carried out. Firstly, the urban low-altitude airspace structure was planned, and the operational levels of eVTOL were clarified; this was followed by introducing the urban dynamic air–ground risk factors and constructing a dynamic risk assessment model containing risk level information; finally, the improved A* algorithm based on the risk cost was employed to plan the eVTOL air route network, which finally realized the purpose of short path length and low total risk. The simulation results showed that the route generated by the improved A* algorithm could reduce the risk cost by at least 30% with a relatively small path cost, which ensured the operation efficiency and safety of eVTOLs and laid the foundation for the further sustainable and green development of urban airspace in the future. [ABSTRACT FROM AUTHOR]

Electric vertical takeoff and landing (eVTOL) aircraft have attracted tremendous attention nowadays due to their flexible maneuverability, precise control, cost efficiency, and low noise. The optimal takeoff trajectory design is a key component of cost-effective and passenger-friendly eVTOL systems. However, conventional design optimization is typically computationally prohibitive due to the adoption of high-fidelity simulation models in an iterative manner. Machine learning (ML) allows rapid decision making; however, new ML surrogate modeling architectures and strategies are still desired to address large-scale problems. Therefore, we showcase a novel regression generative adversarial network (regGAN) surrogate for fast interactive optimal takeoff trajectory predictions of eVTOL aircraft. The regGAN leverages generative adversarial network architectures for regression tasks with a combined loss function of a mean squared error (MSE) loss and an adversarial binary cross-entropy (BC) loss. Moreover, we introduce a surrogate-based inverse mapping concept into eVTOL optimal trajectory designs for the first time. In particular, an inverse-mapping surrogate takes design requirements (including design constraints and flight condition parameters) as input and directly predicts optimal trajectory designs, with no need to run design optimizations once trained. We demonstrated the regGAN on optimal takeoff trajectory designs for the Airbus A 3 Vahana. The results revealed that regGAN outperformed reference surrogate strategies, including multi-output Gaussian processes and conditional generative adversarial network surrogates, by matching simulation-based ground truth with 99.6% relative testing accuracy using 1000 training samples. A parametric study showed that a regGAN surrogate with an MSE weight of one and a BC weight of 0.01 consistently achieved over 99.5% accuracy (denoting negligible predictive errors) using 400 training samples, while other regGAN models require at least 800 samples. [ABSTRACT FROM AUTHOR]

The successful integration of Li-ion batteries in the automotive industry paved the way for their integration into a new generation of aircraft with zero emission. However, potential hazards associated with Li-on batteries are a major concern for the safety-critical aerospace sector. Removing or reducing the hazards from Li-ion batteries while preferable, requires fundamental changes to the battery chemistry. Another way to address this is the implementation of fault diagnostics and prognostics for forecasting or detecting the presence of faults before an aircraft is airborne. This article, part of a three-part series, presents a novel algorithm exploiting the data collected while charging a battery pack for diagnosing faults. The algorithm works off-board, thus not adding any computational burden or weight to the aircraft while minimising aircraft turn-around time, which is crucial for commercial flight operation. This paper presents the underlying method of the algorithm involving the computation of resistance, charge energy and incremental capacity curve using the charging data followed by a combined horizontal and vertical comparative scheme for diagnosis of faults. The performance of the proposed algorithm was validated via module-level experiments considering three cell inactivation faults. Results indicated that the algorithm successfully segregated faulty and unfaulty cells in multiple test scenarios with different number of faults in a laboratory-assembled module. Upon testing the algorithm in experiments conducted using a real-life aerospace battery module, there was a slight reduction in the performance, attributed to greater thermal variation. Nevertheless, the results indicated promising prospects for practical implementation in eVTOL batteries.

In the present study, a performance analysis of three different VTOL configurations is presented within an urban air mobility context. A classical lightweight helicopter was employed as a reference configuration to design a dual-rotor side-by-side helicopter and a hexacopter drone layout. An analytical model based on general momentum and blade element theories was developed for single- and multiple-rotor configurations in horizontal and vertical flight conditions. Suitable battery pack and electric motor designs were produced to evaluate the endurance and range of the different configurations for a specific mission. This paper provides fundamental insights into the endurance and range capabilities of multiple-rotor unmanned aerial vehicles (UAVs) and a qualitative discussion on the safety and acceptability features of each configuration implemented in an advanced air mobility context. As a result, the side-by-side helicopter configuration was identified as the best solution to be introduced within urban environments, fulfilling all the performance and mission requirements.

Electric tilt-wing flying cars are an efficient, economical, and environmentally friendly solution to urban traffic congestion and travel efficiency issues. This article addresses the high energy consumption and obstacle interference during the takeoff phase of the tilt-wing eVTOL (electric Vertical Takeoff and Landing), proposing a trajectory planning method based on energy minimization and obstacle avoidance. Firstly, based on the dynamics analysis, the relationship between energy consumption, spatial trajectory, and obstacles is sorted out and the decision variables for the trajectory planning problem with obstacle avoidance are determined. Secondly, based on the power discretization during the takeoff phase, the energy minimization objective function is established and the constraints of performance limitations and spatial obstacles are derived. Thirdly, by integrating the optimization model with the SLSQP (Sequential Least Squares Quadratic Programming algorithm), the second-order sequential quadratic programming model and decision variable update equations are derived, establishing the solution process for the trajectory planning problem of the tilt-wing eVTOL takeoff with obstacle avoidance. Finally, the Airbus Vahana A3 is taken as an example to verify and validate the effectiveness, stability, and robustness of the model and optimization algorithm proposed. The validation results show that the OTPEM (obstacle avoidance trajectory planning methodology based on energy minimization) can effectively handle changes in the takeoff end state and exhibits good stability and robustness in different obstacle environments. It can provide a certain reference for the three-dimensional obstacle avoidance trajectory planning of Airbus Vahana A3 and other tilt-wing eVTOL trajectory planning problems.

Recently, electric vertical take-off and landing (eVTOL) aircraft have become a top priority for urban air transportation due to their ability to overcome urban ground traffic congestion. In this research, a new type of scaled lift–cruise ‘Dragonfly’ has been designed. The ‘Dragonfly’ combines the characteristics of an octocopter and a fixed-wing aircraft. Compared with the same type of eVTOL aircraft, it has a longer wingspan and a more stable aircraft structure, it can not only take off and land vertically without the need for a runway, but also fly quickly in a straight line and hover in mid-air. In order to ensure the success of the flight test, it was also simulated in this paper. A simulation scenario highly fitting with the flight test environment of eVTOL is designed in the Gazebo simulation platform, and then combined with the PX4 flight control platform, the system SITL of the constructed aircraft simulation model is carried out on the Gazebo platform, Finally, simulation flight test data for accurate analysis are obtained, the accuracy and stability of the control algorithm are fed back, and scientific support for the follow-up ‘Dragonfly’ aircraft hardware-in-the-loop simulation and physical flight test is provided.

The transportation of patients in emergency medical situations, particularly in rural areas, often faces significant challenges due to long travel distances and limited access to healthcare facilities. These challenges can result in critical delays in medical care, adversely affecting patient outcomes. Addressing this issue is essential for improving survival rates and health outcomes in underserved regions. This study explored the potential of advanced air mobility to enhance emergency medical services by reducing patient transport times through the strategic placement of vertiports. Using North Dakota as a case study, the research developed a GIS-based optimization workflow to identify optimal vertiport locations that maximize time savings. The study highlighted the benefits of strategic vertiport placement at existing airports and hospital heliports to minimize community disruption and leverage underutilized infrastructure. A key finding was that the optimized mixed-mode routes could reduce patient transport times by up to 21.8 min compared with drive-only routes, significantly impacting emergency response efficiency. Additionally, the study revealed that more than 45% of the populated areas experienced reduced ground travel times due to the integration of vertiports, highlighting the strategic importance of vertiport placement in optimizing emergency medical services. The research also demonstrated the replicability of the GIS-based optimization model for other regions, offering valuable insights for policymakers and stakeholders in enhancing EMS through advanced air mobility solutions.