Parameter Design and Predictive Antiwindup of Double Closed-Loop Control for DC Three-Stage Generator in More Electric Aircraft

Optimal dispatch of an electricity-thermal-hydrogen microgrid for zero-carbon airport operations with electric and hydrogen aircraft

Early integration of quadratic programming-based power split control in electric aircraft charging system design

State of charge prediction for lithium-ion batteries in electric aircraft based on self-supervised informer

A comprehensive review of sharkskin-inspired surfaces and riblet structures (also known as denticles) is conducted which is motivated by the desire to enhance aerodynamic efficiency and sustainability in modern aviation. Inspired by natural sea creatures like sharks, biomimetic surface alterations aim to reduce drag by altering the flow behavior around aerodynamic surfaces. This approach has gained increasing attention as a promising method for improving aircraft performance, particularly due to its direct impact on reducing fuel consumption. Following the literature review, a simple case study is presented to depict the suitability of riblet applications. The results demonstrated that riblet structures (denticles) can lead to significant drag reduction and, hence enhanced aerodynamic performance. These surface modifications not only can benefit conventional aircrafts but also offer a great promise for novel air vehicles, including unmanned aerial systems, electric aircraft, and urban air mobility platforms, where efficiency and extended range are critical. These findings highlight the potential of biomimetic surface designs as an effective solution in the development of next-generation aerospace systems.

Thermal enhancement and energy minimization using Powell–Eyring nanofluid flow in PTSC for solar-powered aircraft: a combined RSM, ANN, and sensitivity analysis

Recently, the Small Low-Altitude Long Endurance (LALE) solar-powered aircraft gained significant attention in the community. A reliable mathematical model of the aircraft and solar radiation should be available to design such a plane. This paper addresses the problem of measuring solar radiation in flight and validating its model. The configuration of the measurement system was described in detail. Moreover, the Multiplex Funcub NG was used as the intermediate research platform. The results of flight tests in two different geographic locations in Poland confirmed that the proposed models allow for the precise prediction of the amount of harvested energy. The maximum solar radiation intensity measured in September at around noon was 829,3 W/m2. Achieving perpetual flight functionality is possible in these conditions, provided that the aircraft has very low power consumption and a high wing aspect ratio. The obtained data can be used in the design process of the AZ-5 solar-powered plane.

This study aims to comparatively analyze the most preferred electric aircraft models in the world as of 2024 based on performance criteria. While previous multi-criteria decision-making (MCDM) applications have predominantly focused on electric vehicles or hybrid energy systems, this research expands the methodological scope by directly applying the Entropy and TOPSIS methods to electric aviation. The findings indicate that battery capacity and motor power are the most decisive factors in aircraft selection, diverging from automotive studies where cost criteria dominate. The results provide a data-driven and objective framework for guiding aircraft design, procurement, and policy-making in the rapidly expanding electric aviation sector. The originality of this research lies in extending MCDM methodologies to a novel and highly relevant field, thereby addressing an important gap in sustainable aviation literature. By positioning the study against prior applications, it demonstrates the methodological adaptability of Entropy and TOPSIS while generating insights with both academic and industrial relevance. However, the study is subject to certain limitations. The analysis relies on manufacturer-provided technical data and excludes prototype and military aircraft models, which may constrain the generalizability of the results. Despite these limitations, the research contributes to the advancement of sustainable aviation by offering a transparent, reproducible, and timely evaluation of commercially available electric aircraft.

To explore the potential of solar energy in the pursuit of a more sustainable aviation sector, this research examines the feasibility of solar photovoltaic systems for battery recharge of electric or electric hybrid aircraft deployed at four airports in North Africa and North, Central, and South Europe, respectively: Cairo International, London Heathrow, Milan Malpensa, and Rome Fiumicino. Employing PVGIS software with Google Maps, a site-specific photovoltaic array can be designed, optimizing module tilt and orientation to maximize solar energy collection across various climatic conditions. The energy production of the photovoltaic systems at the selected airports is compared to the energy demand required for the annual recharge of the batteries (28 MWh each) used in a widely popular medium-range aircraft, the Airbus A320. Although the calculated amount of energy, allowing for daily capacities ranging from 6 to 10 batteries on average, is insufficient to support the extensive demand associated with the typical air traffic in such airports, the potential of solar energy to decarbonize aircraft seems an appropriate approach to be pursued. Locations with limited solar access necessitate hybrid solutions, especially in sunny regions.

The integration of non-intrusive load monitoring (NILM) into solar-powered aviation systems presents a transformative approach for achieving sustainable, lightweight, and intelligent flight operations. However, the sector’s stringent constraints on weight, latency, and computational resources pose critical challenges to real-time NILM deployment. This study develops a resource-efficient machine learning framework that systematically evaluates six machine learning (ML) and deep learning (DL) models using high-resolution (200 kHz) power data that capture both transient and steady-state load characteristics across all flight phases. Advanced preprocessing techniques—comprising moving average smoothing and non-overlapping downsampling—were applied to suppress noise while preserving essential features. The comparative analysis reveals that K-Nearest neighbors (KNN) delivers the most effective balance between accuracy and computational cost, achieving an R² of 0.9403 with an execution time of 0.20 s, substantially outperforming ensemble models such as random forest (RF) and XGBoost in real-time feasibility. Conversely, the hybrid CNN-LSTM architecture attained the lowest mean squared error (MSE = 0.0048) and superior temporal sensitivity but required 271.53 s, demonstrating its suitability for offline analysis rather than onboard deployment. Through comprehensive hardware-in-the-loop validation using Opal-RT and Launchpad-F28379D DSP controllers, the framework verified appliance-level disaggregation accuracy under dynamic flight scenarios. The findings underscore a critical accuracy–efficiency trade-off in NILM model selection, establishing that traditional ML algorithms can outperform complex DL models when optimized for real-time, resource-constrained environments. This research provides actionable design insights for next-generation solar-powered aircraft energy management systems, demonstrating that model selection must prioritize computational efficiency, predictive reliability, and real-time responsiveness to enable sustainable and intelligent aviation energy control.

Vibration analysis of hole-containing laminated composite combined structures in electric aircraft using an area scan-fitting approach

Efficiency-Enhanced Distributed Aggregated Power Management for Multistack Fuel Cell Hybrid Propulsion Systems in Electric Aircraft

A composite laminated tail structure, specifically a vertical stabilizer (composite laminated vertical stabilizer, CLVS), employing a double-double layup with in situ mesh embedding of Nitinol element wires, was developed for broadband vibration control. Finite-element and Rayleigh–Ritz modal analyses, coupled with the Galerkin truncation and harmonic balance method (GTM-HBM) and hammer-impact tests, accurately predicted and validated natural frequencies, mode shapes, and the nonlinear dynamic response of the tail stabilizer. Broadband sweep tests in the aviation temperature range show 20–50% vibration reduction from 40 to 400 Hz, with damping retained at high temperature. A one-step molding process embeds Nitinol wires and ropes directly into the composite layup, eliminating secondary bonding and stress concentrations while enhancing stabilizer integrity. This integrated workflow, from ply and mesh design to dynamic modeling and experimental validation, provides a rapid design tool for multifunctional composite structures in electric aircraft under complex mechanical and thermal loads. This approach can be applied to broadband variable-temperature vibration control in composite structures of electric aircraft, paving new pathways for the development of multifunctional aviation structures.

Energy management strategy for parallel hybrid electric aircraft considering SOC sustainment

Enhanced power density and energy-efficient high-speed permanent magnet starter-generator using multi-physics optimization strategies for future electric aircraft

Propeller slipstream driven air–liquid hybrid cooling system for electric aircraft power cabin thermal management

Novel two-phase based cooling systems for fuel cell electric aircraft

Emerging applications, such as electric aircraft and ships, demand rechargeable batteries with high specific energy. However, current lithium (Li) ion batteries fall significantly short in this regard. Even with Li metal batteries, achieving a high cell-level specific energy (e.g. ≥600 Wh kg−1) remains a significant challenge. In this study, a synergistic strategy integrating a precisely engineered carbonate-based gel-solid-state electrolyte with a surface-modified Li is proposed. Our in-situ gelation technique confines unstable free carbonate solvent molecules, thereby suppressing the electrolyte-induced parasitic reactions. Furthermore, a bicontinuous gradient polymer layer that regulates Li deposition and improves moisture/oxygen resistance is introduced, enabling damage-free Li processing and avoiding harsh production requirements. As a result, our 11 Ah-level Li metal battery achieves a high specific energy of 604.2 Wh kg−1 (626.4 Wh kg−1 excluding the packaging materials) and operates for over 100 cycles with an energy retention of 92.83% under lean electrolyte conditions (0.85 g Ah−1). This work offers a practical strategy for the scalable production of long-cycle Li metal batteries with high specific energy for broad future applications.

The transition to electric aircraft for zero-emission transport requires integrating thermal management systems for high-performance batteries without incurring significant weight, balance, or aerodynamic penalties. This study focuses on the aerodynamic penalties associated with air-cooling systems that can compound the presently unavoidable reduction in endurance imposed by current battery energy density limitations. Building on previous research into battery installation layouts and internal cooling flows, this study is the first to investigate the lift-to-drag (L/D) optimisation for the multiple wing-mounted inlets and outlets necessary for air-cooling batteries in the wing of an electrified aircraft. Wing leading-edge inlets and NACA (National Advisory Committee for Aeronautics) ducts were analysed by systematically varying their layout, number, and dimensions. The analysis evaluated their effects on the wing’s lift, drag, and moment to maximise the L/D. Multiple highly efficient simulation test designs were developed to screen for the main factors to identify the best inlet and outlet configuration, resulting in 66 different Computational Fluid Dynamics (CFD) simulations in Ansys Fluent. Following this, three CFD verification cases of the best configuration were conducted to verify the cooling effect by combining both internal and external flow simulations with heat generation. Compared to the baseline wing of the carbon combustion aircraft, the best configuration caused a 1.75% reduction in L/D, range, and endurance. While the aerodynamic penalty is now minimised, the internal battery pack layout requires further optimisation to re-establish uniform cooling across the battery pack. Designers may still be able to separate the CFD analysis of the internal and external flow regimes with idealised inlets and outlets; however, more whole-field CFD iterations are needed to guide such subdivision to a viable and safe design for wing-mounted batteries. Further, the margins are such that wing-mounted electrification warrants careful instrumented validation in an aircraft. These findings provide crucial design guidance for sustainable aviation, particularly to enable after-market electrification projects.

With the development of society and increasing changes in energy demands, safety issues concerning lithium-ion batteries in applications such as electric aircraft have garnered significant attention. To investigate the influence of aviation propulsion lithium-ion battery system design on safety performance, this research introduces the concept of the Thermal Runaway Explosion Index and applies it to the quantitative assessment of lithium-ion battery system safety design. Through experimental and theoretical analyses, utilizing self-built modules for lithium-ion battery thermal runaway, gas explosion characteristics testing, and thermal runaway containment testing, a quantitative assessment was conducted on the inherent safety, operational safety, and protective safety of the lithium-ion battery system. The results demonstrate that protective design plays a critical role in reducing the thermal runaway explosion index. Specifically, the protective effect achieved by applying a fireproof coating is superior to that obtained by increasing the thickness of the top plate. Moreover, the E85S15B3 coating exhibits the optimal performance in reducing both temperature and weight. Following correction with 1mm thick E85S15B3 coating protection, the thermal runaway explosion index is 0.0942. Compared to the scenario without a protective top plate, the maximum temperature drops by 55.80%, and the weight of the battery top plate can be reduced by 36.59% under equivalent volume conditions. The conclusion of this research provides a theoretical basis and practical guidance for the hazard assessment and system safety design of aviation lithium-ion battery systems.