Aircraft Subsystems Research Articles

Prognostics of aerospace electromechanical actuators: comparison between model-based metaheuristic methods

Electro-Mechanical Actuators (EMAs) deployment as aircraft flight control actuators is an imperative step towards more electric concepts, which propose an increased electrification in aircraft subsystems at the expense of the hydraulic system. Despite the strong benefits linked to EMAs adoption, their deployment is slowed down due to the lack of statistical data and analyses concerning their often-critical failure modes. Prognostics and Health Management (PHM) techniques can support their adoption in safety critical domains. A very promising approach involves the development of model-driven prognostics methodologies based on metaheuristic bio-inspired algorithms. Evolutionary (Differential Evolution (DE)) and swarm intelligence (particle swarm (PSO), grey wolf (GWO)) methods are approached for PMSM based EMAs. Furthermore, two models were developed: a reference, high fidelity model and a monitoring, low fidelity counterpart. Several failure modes have implemented: dry friction, backlash, short circuit, eccentricity and proportional gain. The results show that these algorithms could be employed in pre-flight checks or during the flight at specific time intervals. Therefore, EMA actual state can be assessed and PHM strategies can provide technicians with the right information to monitor the system and to plan and act accordingly (e.g. estimating components Remaining Useful Life (RUL)), thus enhancing the system availability, reliability and safety.

A Design Model for Electric Environmental Control System in Aircraft Conceptual and Preliminary Design

In present decades, the need for a more efficient air transport system is driving towards more electric aircraft subsystems. Electrified subsystems offer the opportunity to optimize the operational performance of systems by reducing the power required by the propulsion system therefore, reducing the fuel burnt. A considerable advantage can be obtained by electrifying the environmental control system which is the most power demanding aircraft subsystem. The paper presents a simplified model to estimate the main performances of the conventional and electrified environmental control system during the aircraft conceptual and preliminary design phases. Different air cycle machine architectures can be designed. The model is divided in two main modules. The first is dedicated to the estimation of the aircraft thermal loads including the effect of solar radiation, the conduction of external air, the presence of passengers and the avionic systems. With the main result of estimating the cabin airflow required to control the temperature and the air quality within the aircraft’s mission profile. The second module of the model designs all major components of the air conditioning pack including the dedicated compressors of the electrified environmental control system. The model requires basic input data that can be easily estimated during the early stages of aircraft design. The model is calibrated using the available data of a conventional system and then applied to the electrified one. The results show the increased efficiency of the electrified system that results from optimizing both pneumatic power generation and the air cycle machine.

Design Optimization of a High-Speed Twin-Stage Compressor for Next-Gen Aircraft Environmental Control System

Abstract The environmental control system (ECS) is the largest auxiliary power consumer, i.e., around 75% of non-propulsive power, among the aircraft subsystems. The adoption of a novel ECS architecture, based on an electrically-driven vapor compression cycle system, can enable a twofold increase of coefficient of performance at cruise conditions, as compared to the conventional air cycle machine. The core of this technology is a high-speed, miniature centrifugal compressor, consisting of two impellers mounted in back-to-back configuration, and running on gas bearings, operating with refrigerant. The fluid dynamic design optimization of the twin-stage compressor, to be installed in the vapor compression cycle test rig under realization at Delft University of Technology, is documented in this paper. First, the scaling analysis for centrifugal compressor is extended to provide guidelines for the design of twin-stage machines. Then, a multi-objective conceptual design optimization is performed by resorting to an in-house reduced-order model (ROM), coupled to a genetic algorithm. The fluid dynamic performance and the structural integrity of the optimal design are assessed by means of a hybrid framework, encompassing computational fluid dynamics and ROMs, and by finite element analysis. The results show that it is possible to design a twin-stage compressor for the target application, featuring an average efficiency higher than 70%, a maximum compression ratio exceeding 9, and an operating range of 0.27 at the design rotational speed, despite the detrimental effects of motor cooling and miniature size.

Reliability prediction for aircraft fleet operators: A Bayesian network model that combines supplier estimates, maintenance data and expert judgement

Reliability prediction is crucial for aircraft maintenance and spare part inventory decisions. These predictions are made based on operational data collected by fleet operators or design life estimates provided by aircraft suppliers. Purely data-driven predictions have limited use especially when the fleet is young, hence the data is scarce. In this case, design life estimates are used for predicting reliability often by assuming a constant failure rate. This strong assumption is not necessarily valid for all components. This paper proposes a Bayesian Network (BN) modelling framework that systematically combines design life estimates, operational data, and expert judgement for reliability prediction of aircraft subsystems. The proposed BN adjusts the design life estimates based on expert judgement regarding supplier and manufacturing quality and revises it based on operational data. We used the BN to predict the reliability of a large aircraft fleet by using failure and maintenance data provided by a large fleet operator. We compared the predictive performance of the BN to using only data-driven approaches and to using only design life estimates provided by the aircraft supplier. The BN model provides consistently accurate reliability predictions compared to design-life estimates and purely data-driven approaches especially when the available data is scarce.

Commercial Aircraft Electrification—Current State and Future Scope

Electric and hybrid-electric aircraft propulsion are rapidly revolutionising mobility technologies. Air travel has become a major focus point with respect to reducing greenhouse gas emissions. The electrification of aircraft components can bring several benefits such as reduced mass, environmental impact, fuel consumption, increased reliability and quicker failure resolution. Propulsion, actuation and power generation are the three key areas of focus in more electric aircraft technologies, due to the increasing demand for power-dense, efficient and fault-tolerant flight components. The necessity of having environmentally friendly aircraft systems has promoted the aerospace industry to use electrically powered drive systems, rather than the conventional mechanical, pneumatic or hydraulic systems. In this context, this paper reviews the current state of art and future advances in more electric technologies, in conjunction with a number of industrially relevant discussions. In this study, a permanent magnet motor was identified as the most efficient machine for aircraft subsystems. It is found to be 78% and 60% more power dense than switch-reluctant and induction machines. Several development methods to close the gap between existing and future design were also analysed, including the embedded cooling system, high-thermal-conductivity insulation materials, thin-gauge and high-strength electrical steel and integrated motor drive topology.

Thermal oxidation deposition characteristics of RP-3 kerosene in serpentine tubes under supercritical pressure

Kerosene is in increasing demand as a coolant in advanced aircraft to cool aircraft subsystem and engine. Unfortunately, during fuel heated process, thermal oxidation deposition accumulates on the surface of cooling channels attributed to the participation of trace species via autoxidation chain reactions. The deposition can weaken heat transfer, block flowing passageway, and even cause the catastrophic aircraft failures. However, most investigations have only considered straight tubes, although more compact serpentine tubes are more practical for applications in aircraft cooling system to save space and enhance heat transfer. In this work, deposition and heat transfer behaviors in straight tube and serpentine tubes with 2, 3 and 4 bending sections were firstly compared. Then, the deposition characteristics in 4-Bend serpentine tubes were analyzed at different outlet fuel temperatures of 400–800 K, mass flow rates of 0.5–1.5 g/s and supercritical pressures of 3–7 MPa. The experimental results indicated that the application of serpentine tubes not only effectively inhibited deposition, but also remarkably enhanced heat transfer. In 4-Bend serpentine tube, the total deposition amount was approximately 24.8% less than that in straight tube. The deposition rate achieved a peak value at bending section because of the strong mass transfer caused by secondary flow. The fuel temperature, which was the dominant factor in thermal oxidation deposition process, influenced the deposition distribution and morphology. As temperature increased from 400 to 800 K, deposition exhibited five main morphologies, ranging from small particles through clusters to dented block deposition. The total deposition amount was directly proportional to the mass flow rate. High system pressure slightly inhibited deposition formation, but resulted in a more dramatic decrease in outlet fuel temperature. Overall, a relatively low supercritical pressure was preferable, considering the deposition and heat transfer performance.

Modelling Green VTOL Concept Designs for Reliability and Efficiency

All-electric and hybrid-electric aircraft are a future transport goal and a possible ‘green’ solution to increasing climate-related pressures for aviation. Ensuring the safety of passengers is of high importance, informed through appropriate reliability predictions to satisfy emerging flight certification requirements. This paper introduces another important consideration related to redundancy offered by multiplex electric motors, a maturing technology which could help electric aircraft manufacturers meet the high reliability targets being set. A concept design methodology is overviewed involving a symbolic representation of aircraft and block modelling of two important figures of merit, reliability, and efficiency, supported by data. This leads to a comparative study of green aircraft configurations indicating which have the most potential now, and in the future. Two main case studies are then presented: an electric tail rotor retrofitted to an existing turbine powered helicopter (hybrid) and an eVTOL aircraft (all-electric), demonstrating the impact of multiplex level and number of propulsion channels on meeting target reliabilities. The paper closes with a summary of the important contribution to be made by multiplex electric machines, well as the advancements necessary for green VTOL aircraft sub-systems, e.g., power control unit and batteries, to improve reliability predictions and safety further.

Wheel-slip estimation for advanced braking controllers in aircraft: Model based vs. black-box approaches

As of today, most aircraft are endowed with Anti-lock Braking Systems that are active during landings and rejected take-off manoeuvres, ensuring the maximum exploitation of road-friction capability. Due to strict certification issues, the braking controller must function using only signals that are local to the landing gear, which is the aircraft sub-system hosting the braking actuators. In the most common scenarios, the only available signals are the wheel speed and the braking pressure. This limited set of information prevents the use of advanced braking control architectures which are now mainstream in the automotive sector, i.e., those based on the regulation of the wheel slip, so that typical aircraft Anti-lock Braking Systems are usually based on the regulation of the wheel deceleration. This paper investigates how a reliable wheel slip estimation can be achieved using wheel speed and braking pressure signals, analysing different wheel slip observers options. In particular, a model-based approach that uses a sliding-mode observer is proposed, together with a black-box approach based on Nonlinear Auto-Regressive models with eXogenous input, with a neural network implementation. Both approaches are tested and compared on experimental data, proving that the obtained estimation performance are adequate for use in closed-loop braking systems.

Optimal Paths for Progressive Aircraft Subsystem Electrification in Early Design

The push for more-electric aircraft (MEA) has motivated numerous studies to quantify and optimize the impact of subsystem electrification in early design phases. Past studies on multi-objective optimization of MEA show a clear benefit over conventional architectures when no constraints are placed on the number of subsystems electrified at once. In reality, aircraft manufacturers are more likely to progressively electrify subsystems over multiple aircraft generations. While step-by-step electrification may lead to suboptimal MEA architectures when compared with scenarios with no such imposition on the number of subsystems electrified, little or no literature was found to address the optimal paths toward such electrification changes. This study proposes a mathematically defensible method to analyze different directions of technology evolution focusing on aircraft subsystem electrification. It seeks to enable decision makers to understand the performance tradeoffs between different electrification paths under different scenarios, constraints, and uncertainties. Certain trends in Pareto-optimal MEA architectures and progressive subsystem electrification order (optimal paths) under uncertainty are discussed.

Optimal Selection of Model Validation Experiments: Guided by Coverage

Abstract Modeling and Simulation (M&S) is seen as a means to mitigate the difficulties associated with increased system complexity, integration, and cross-couplings effects encountered during development of aircraft subsystems. As a consequence, knowledge of model validity is necessary for taking robust and justified design decisions. This paper presents a method for using coverage metrics to formulate an optimal model validation strategy. Three fundamentally different and industrially relevant use-cases are presented. The first use-case entails the successive identification of validation settings, and the second considers the simultaneous identification of n validation settings. The latter of these two use-cases is finally expanded to incorporate a secondary model-based objective to the optimization problem in a third use-case. The approach presented is designed to be scalable and generic to models of industrially relevant complexity. As a result, selecting experiments for validation is done objectively with little required manual effort.

Development of a Flexible Framework Multi-Design Optimization Scheme for a Hand Launched Fuel Cell-Powered UAV

This paper presents different methods for the design of a hand-launchable, fixed wing, fuel cell-powered unmanned aerial vehicle (UAV) to maximize flight endurance during steady level flight missions. The proposed design methods include the development of physical models for different propulsion system components. The performance characteristics of the aircraft are modeled through empirical contributing analyses in which each analysis corresponds to an aircraft subsystem. The contributing analyses are collected to form a design structure matrix which is included into a multi-disciplinary analysis to solve for the design variables over a defined design space. The optimal solution is found using a comprehensive optimization tool developed for long endurance flight missions. Optimization results showed a significant improvement in UAV flight endurance that reached up to 475 min with take-off ratio equals to 59 min/kg. Wind tunnel and bench-top tests and HiL simulation tests are performed to validate the results obtained from the optimization tools. Validated optimization results showed an increase of the overall UAV flight endurance by 19.4% compared to classical approaches in design methods.

Partitioned artificial immune system for detection and identification of autonomous flight vehicle abnormal conditions

PurposeAn artificial immune system (AIS) for the detection and identification of abnormal operational conditions affecting an unmanned air vehicle (UAV) is developed using the partition of the universe approach. The performance of the proposed methodology is assessed through simulation within the West Virginia University (WVU) unmanned aerial system (UAS) simulation environment.Design/methodology/approachAn AIS is designed and generated for a fixed wing UAV using data from the WVU UAS simulator. A novel partition of the universe approach augmented with the hierarchical multiself strategy is used to define the self, within the AIS paradigm. Several 2-dimensional and 3-dimensional commanded trajectories are simulated under normal and abnormal conditions affecting actuators and sensors. Data recorded are used to build the AIS and develop an abnormal condition detection and identification scheme for the two categories of subsystems. The performance of the methodology is evaluated in terms of detection and identification rates, false alarms and decision times.FindingsThe proposed methodology for UAV abnormal condition detection and identification has the potential to support a comprehensive and integrated solution to the problem of aircraft subsystem health management. The novel partition of the universe approach has been proven to be a promising alternative to the previously investigated clustering methods by providing similar or better performance for the cases investigated.Research limitations/implicationsThe promising results obtained within this research effort motivate further investigation and extension of the proposed methodology toward a complete system health management process, including abnormal condition evaluation and accommodation.Practical implicationsThe use of the partition of the universe approach for AIS generation may potentially represent a valuable alternative to current clustering methods within the AIS paradigm. It can facilitate a simpler and faster implementation of abnormal condition detection and identification schemes.Originality/valueIn this paper, a novel method for AIS generation, the partition of the universe approach, is formulated and applied for the first time for the development of abnormal condition detection and identification schemes for UAVs. This approach is computationally less expensive and mitigates some of the issues related to the typical clustering approaches. The implementation of the proposed approach can potentially enhance the robustness of UAS for safety purposes.

Factorial Study on Seated Aircraft Passengers’ Body Heat Harvesting

The increased electrical power demand for aircraft subsystems drives the search for a new alternative onboard power source. One of the solutions that have been proposed is the heat energy harvesting of the aircraft passengers’ body. Taking advantage of the Seebeck effect phenomenon, the dissipated heat from seated passengers’ body can be converted into useful electrical power using a thermoelectric generator. The main objective of this study is to establish whether the performance of such heat harvesting system is highly dependent on the passengers’ body features and cabin environmental temperature. An experiment with 10 volunteers using a mock-up aircraft passenger cabin setup is conducted and the temperature readings when they are seated on the aircraft seat is recorded through installed thermal sensors. The collected data is then analyzed using Analysis of Variance (ANOVA) method to find the factorial contribution of volunteers’ age, weight, height and gender, plus the ambient temperature, on the performance of the heat harvesting system. In this case, potential performance of such energy harvesting is measured by the maximum temperature differential that can be possibly obtained. Based on ANOVA results, the passengers’ weight, height, age and gender do not have a significant effect on the temperature differential. This can be taken to imply that the heat harvesting performance is not highly dependent on the passengers’ characteristics. In contrast, ambient temperature is found to be influential, meaning that operational performance of such heat harvesting mechanism can be controlled through appropriate setting of the cabin environmental temperature.

Исследование способов повышения безотказности пассивно резервированных подсистем управления летательными аппаратами с учетом допусков

The paper studies the reliability of passively redundant subsystems of aircraft, taking into account tolerances for a decrease in their output parameters in case of sudden component failures. The influence of the reliability values of elements, tolerances of two levels and the redundancy ratio 
 on the reliability of passively redundant subsystems as a whole have been investigated; the examples of such subsystems have been given. There have been presented the results of analysis 
 of the aircraft subsystems features with allowance for tolerances. First of all, these include the availability of technical specifications and realized tolerances determined by the reservation structure; implementing each tolerance with different values of the multiplicities of redundancy; using the main tolerance grid by multiple backup methods; presence of critical probabilities narrowing the reliability range of the elements, where this type of reservation is beneficial from the range 
 0–1 to the range of the supercritical area (pkr–1). The influence of the element reliability values, tolerances of two levels and the redundancy ratio on the failure-free operation of passively redundant subsystems in general and in supercritical areas has been investigated. It is shown that the minimum redundancy multiplicities in the interests of increasing the reliability of the considered subsystems of aircraft are advantageous to use only with large tolerances and low probabilities of failure-free operation of their elements. Under close tolerances and any reliability values of elements, as well as with large tolerances (more than 25%), high reliability values of this class of aircraft subsystems can be achieved only with large redundancy multiplicities. It has been inferred that there are extreme reliability differences of a passively redundant subsystem and its element, which 
 allows to set the task of developing highly reliable passively redundant subsystems of aircraft taking into account tolerances from relatively unreliable elements.

Power Management Problem for Civil Aircraft under More Electric Environment

The civil aviation industry is moving toward the more electric aircraft (MEA) which is to use electrical power to meet the load demands on multiple aircraft subsystems which are conventionally driven by other power resources. Thus, there will be introduced a large amount of new electrical power demands which are safety-critical for aircraft’s flight and this may lead the challenge for a reliable and efficient power management problem (PMP): the balance between the aircraft power supply and demands while minimizing the operation costs. To cope with the PMP for civil aircraft under more electric environment, in this paper, we explicitly give a detailed and complete modeling of all power supply resources (fuel and battery) and safety-critical electrical loads and cast the PMP as a mixed-integer nonlinear programming problem; we develop a practical solution methodology for the application on the real civil MEA. The proposed formulation and solution algorithm can give an efficient power schedule result with the minimal fuel and battery operation cost through a smart codispatch between the gas turbine generator, storage devices, and all electrical loads of MEA. Numerical testing results based on one real civil aircraft case demonstrate the economic and operational effectiveness.

An Integrated Scheme of a Smart Net Capturer for MUAVs

Micro Unmanned Aerial Vehicles (MUAVs), including consumer-grade ones, have been frequently threatening urban low-altitude security in recent years. This article analyses the necessity to develop specialized technology of anti-MUAVs. Then the article proposes an engineering scheme of a Smart Weapon Capturing MUAVs (SWCM) in an automatic and soft-killing way. The scheme includes a ground subsystem and an aircraft subsystem. The ground subsystem mainly includes optical sighting equipment and handheld launch control device. The aircraft subsystem includes guidance, control, structure, aerodynamic, etc. The design principle of this scheme embodies the technical characteristics of autonomy, high efficiency, low cost and civil-military dual use. The validity of the smart weapon system design is proved by numerical simulations and experiments, and its application is also prospected.

Energy Optimization Analysis of Turbofan Engine for More-Electric Civil Aircraft

The civil aviation industry is moving into the more-electric environment where the civil aircraft uses electricity to meet the multiple energy demands of the associated aircraft subsystems. The civil aircraft’s turbofan engine, which is the largest energy supply system of civil aircraft, will thus utilize more fuel resource to provide increased electric energy besides of its conventional responsibility of maintaining the fundamental thrust requirements by aircraft. This will introduce new challenge for the energy optimization analysis of aircraft turbofan engine: it was nearly a simple optimal setting of engine’s component parameters for keeping required thrust, but under the more-electric environment it will become an optimization problem in order to minimize the fuel consumption while obeying the multiple constraints by thermodynamic limits of turbofan engine and by varying electric power demands associated with the flight profile of aircraft. We present a complete modeling in this paper for the energy optimization analysis of turbofan engine for more-electric civil aircraft and formulate it as a nonlinear programming form. We propose an algorithm based on Benders decomposition method to solve this problem; the numerical results demonstrate the economic effectiveness of the proposed modeling and algorithm.

A stochastic air combat logistics decision model for Blue versus Red opposition

AbstractTechnologically advanced aircraft rely on robust and responsive logistics systems to ensure a high state of operational readiness. This paper fills a critical gap in the literature for combat models by closely relating effectiveness of the logistics system to determinants of success in combat. We present a stochastic diffusion model of an aerial battle between Blue and Red forces. The number of aircraft of Blue forces aloft and ready to be aloft on combat missions is limited by the maximum number of assigned aircraft, the reliability of aircraft subsystems, and the logistic system's ability to repair and replenish those subsystems. Our parsimonious model can illustrate important trade‐offs between logistics decision variables and operational success.

Distributed Model Predictive Control for More Electric Aircraft Subsystems Operating at Multiple Time Scales

This article considers predictive control of the jet engine and electrical power distribution system of a more electric aircraft (MEA) with asynchronous distributed controllers. The shafts of the engine spools are mechanically coupled to the electrical generators of the microgrid, linking the dynamics of the two subsystems. As the subsystems and their controllers are designed by different entities, the preservation of subsystem privacy must be an integral part of any coordination mechanism and, due to the underlying subsystems having differing time scales in their dynamics, the subsystem control updates are not guaranteed to be synchronized. To address these requirements, a distributed model predictive control (D-MPC) algorithm based on the alternating direction method of multipliers (ADMM) is proposed, which accounts for and exploits the differing control update rates of the engine and power subsystem controllers while preserving privacy. An extension to the Algorithm that seeks to minimize the required communication volume by downsampling the interactions to the rate of the engine time scale is also presented. Simulation results on a high-fidelity nonlinear system model demonstrate that the distributed controllers can outperform a decentralized controller and their performance can match that of a fully centralized controller.

On-Board Microgrids for the More Electric Aircraft

Aircraft transportation holds a tremendous importance in today’s society. Considering the international roadmaps for the intensification of the air travel and the targets concerning the environmental impact, aircraft efficiency has been in the spotlight of scientific research for more than two decades. Electrification of the aircraft subsystems and, in the future, of the propulsion appears to be the way forward to reach these ambitious goals. This Special Section collects contributions related to the more electric aircraft (MEA) technologies, from the power systems to the actuation systems.