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Demand for more environmentally friendly flight has been driving innovation in propulsion systems. HASTECS proposed designs that increase the efficiency and decrease the weight of on-board power components in hybrid propulsion systems.Merging expertise in electrical, chemical and thermal engineering, the EU-funded HASTECS project assessed and optimised architectures for hybrid propulsion – an evolving technology that could yield many reductions in CO2 emissions in future aircraft. As in hybrid cars, the technology supplements traditional fuel-burning internal combustion engines with electric motors that use energy from auxiliary power sources such as batteries or fuel cells. Despite their promising potential, electrical systems require advances in power electronics to handle the ever-increasing loads and need to dissipate the heat created by losses within the electrical power chain. Furthermore, the additional weight and fuel consumption introduced by the extra electric components need to be offset by very high-energy performance systems.“Focusing on regional aircraft designed to fly up to 70 passengers on short-haul routes, we developed models and designed tools to optimise hybrid propulsion. Our activities ranged across the whole spectrum of hybrid electric power chain: electric machines, cooling, power electronics and thermal management,” notes Xavier Roboam, research director at the LAPLACE laboratory at the University of Toulouse in France and HASTECS coordinator.

This work provides a simple and straightforward method based on Markov chains to generate a large number of probabilistic energy production and demand profiles when historical measurements are available. The method is intended for energy modelers seeking a simple generation approach to test different design and operation methods for microgrids without spending too much time in this generation phase. Results show that the proposed method can capture the main statistical features and the temporal variability of real data at both long and short time scales, despite the method's simplicity.

National audience; Nous synthétisons, dans cet article, les principaux tenants de l’électrification (de l’hybride à l’électrique) de la propulsion des aéronefs. Après une présentation générale du contexte, situant les gains potentiels au plan aérodynamique et énergétique, nous présentons les principales architectures hybrides et électriques dont la conception se doit d’être abordée avec une vision multidisciplinaire, particulièrement riche de sens, mais également complexe. Dans ce contexte, nous détaillons un exemple de conception multiphysique par optimisation (MDO) se basant sur le projet européen ‘’HASTECS’’ qui traite de la conception technologique des principaux constituants de la chaîne de propulsion. L‘accent est mis enfin sur la conception intégrée par optimisation de l’ensemble de cette chaine propulsive, permettant de mettre en regard les principaux degrés de liberté et contraintes de cette optimisation avec les performances sous-jacentes pour le système de propulsion complet.

Nous synthétisons, dans cet article, les principaux tenants de l’électrification (de l’hybride à l’électrique) de la propulsion des aéronefs. Après une présentation générale du contexte, situant les gains potentiels au plan aérodynamique et énergétique, nous présentons les principales architectures hybrides et électriques dont la conception se doit d’être abordée avec une vision multidisciplinaire, particulièrement riche de sens, mais également complexe. Dans ce contexte, nous détaillons un exemple de conception multiphysique par optimisation (MDO) se basant sur le projet européen ‘’HASTECS’’ qui traite de la conception technologique des principaux constituants de la chaîne de propulsion. L‘accent est mis enfin sur la conception intégrée par optimisation de l’ensemble de cette chaine propulsive, permettant de mettre en regard les principaux degrés de liberté et contraintes de cette optimisation avec les performances sous-jacentes pour le système de propulsion complet.

This paper focuses on the integrated design and control under uncertainties of a distributed energy system (DES): the future energy demand and production as well as the electricity tariff are not perfectly known while sizing and operating the system. To address this question, a two-stage stochastic programming model is implemented where uncertainties are modelled as random variables and the quality of the solutions is assessed on a common "out-of-sample'' simulator. The results show that the method provides designs which are consistent with a given risk measure (expectation, worst case, etc.).

The aircraft electric network is a complex system, consisting of many different elements integrated to form a unique entity, designed to perform a well-defined mission. In the current state, the network conceptual design is based on standards defined by the aircraft manufacturer. As a consequence, electric subsystem suppliers are doing local optimizations to fulfill these standards in a separated way through a “mechanistic approach”. This results in a set of optimized subsystems which is not necessarily “optimal” with respect to the network level. To overcome this problem, we present a design approach called EPFM (Extended Pareto Front Method) based on separated subsystem optimizations which aims at finding an optimal configuration of the electrical network at the system level. The EPFM is discussed with regard to the computational cost and the collaboration requirements in the aeronautical industrial context and compared with the classical mechanistic approach.

The environmental context of aeronautics (less CO2, les fuel burn, acceptability) is “drastically changing” and electrification of future aircrafts becomes a key driver. Whatever if non propulsive systems (

International audience; The impact of power subsystem design on aircraft performance has traditionally been assessed during an aircraft’s conceptual design phase via estimates based on past design references and databases. With the advent of the more/all electric aircraft (M/AEA), the need to more fully integrate electrical power subsystems into the overall aircraft system greatly increases. However, determining impacts on fuel consumption and other aircraft level benefits during the conceptual design phase becomes significantly more difficult and cannot be fully realized on the basis of past design references and databases since they are insufficient for addressing the impacts of the new architectures and technologies involved. To address this lacuna, a comprehensive framework of methodologies, models, and tools is needed for this phase of the design process to quickly, efficiently, and with sufficient fidelity assess and optimize the mission-level conceptual design of the electrical power subsystem (EPS) and its integration into the overall aircraft system. This also requires a rethinking of the thermal management subsystem (TMS) due to increased heat loads relative to the EPS and the possibility of TMS electrification, which in turn requires a simultaneous consideration of both subsystems during the integration and conceptual design phase of system assessment and optimization. Further discussion on why this is of importance and on why we need such a framework now is given in this paper.

PurposeThe effectiveness of full passive wind turbine (WT) systems has been recently demonstrated. Such low cost and reliable structures without active control and with a minimum number of sensors can be efficient only if the system design parameters are mutually adapted through an integrated optimal design approach. The purpose of this paper is to analyze the effectiveness of a passive WT with regard to the variations of PMSG electrical parameters.Design/methodology/approachThis work is more specifically devoted to the sensitivity analysis of a passive WT system according to the electrical variable variations of a Permanent Magnet Synchronous Generator (PMSG). It also investigates the interest of a robust design approach for reducing the sensitivity of the WT efficiency to the most influencing variables.FindingsIt is shown that efficiency of the passive WT system is rather sensitive to the variation of the stator flux and DC voltage at the system output.Originality/valueA robust design approach is investigated in order to reduce the passive WT sensitivity to the stator flux and DC voltage variations.

This work deals with an Integrated Optimal Design (IOD) methodology of a full passive wind turbine system offering very good tradeoff in terms of cost, reliability and performance. Without active electronic device (power and MPPT control), efficiency of such architecture can only be obtained if all devices are mutually adapted: this can be achieved through an Integrated Optimal Design (IOD) approach. Wind energy extraction as whole losses are then optimized from a multiobjective genetic algorithm which aims at concurrently optimizing the energy efficiency while reducing the weight of the wind turbine system given a wind cycle. The whole system (turbine, generator, diode reducer, battery DC bus) has been modeled to obtain optimization results and finally to select a particular solution for an experimental validation. On the one hand, the obtained results put forward coherency between models and experience. On the other hand, given a reference wind cycle, it is possible to obtain optimal devices (generator – reducer – DC bus) whose energy efficiency is nearly equivalent to the ones obtained with active and more complex systems with MPPT control. Based on a sensitivity analysis of performance versus parametric uncertainties, one major contribution deals with a design methodology integrating robustness issues inside the optimization process.; Ce travail présente une méthodologie de Conception Optimale Intégrée (COI) d'un système éolien entièrement passif pour offrir un compromis coût- fiabilité - performance très satisfaisant. En l'absence d'électronique de puissance et de contrôle par MPPT, le dispositif n'est efficace que si l'adaptation des constituants est optimale. L'extraction de vent ainsi que les pertes globales du système sont donc optimisées à l'aide d'un algorithme génétique multicritère pour augmenter l'efficacité énergétique et minimiser la masse pour un profil de vent donné. La globalité du système(turbine – génératrice – redresseur - stockage) a été modélisée pour parvenir aux résultats d'optimisation et à la réalisation d'un prototype correspondant à une solution particulière. Les résultats obtenus montrent, d'une part, la cohérence entre modèles et expérience. D'autre part, il est possible, pour un profil de vent donné, d'obtenir une configuration optimale de l'ensemble génératrice – pont redresseur présentant des caractéristiques analogues à celles d'architectures « actives » plus complexes, associées à des lois de contrôle par MPPT. Suite à une analyse de sensibilité des performances aux paramètres, une de nos contributions concerne une approche de conception intégrant les questions de robustesse au sein même du processus d'optimisation.

This work deals with an Integrated Optimal Design (IOD) methodology of a full passive wind turbine system offering very good tradeoff in terms of cost, reliability and performance. Without active electronic device (power and MPPT control), efficiency of such architecture can only be obtained if all devices are mutually adapted: this can be achieved through an Integrated Optimal Design (IOD) approach. Wind energy extraction as whole losses are then optimized from a multiobjective genetic algorithm which aims at concurrently optimizing the energy efficiency while reducing the weight of the wind turbine system given a wind cycle. The whole system (turbine, generator, diode reducer, battery DC bus) has been modeled to obtain optimization results and finally to select a particular solution for an experimental validation. On the one hand, the obtained results put forward coherency between models and experience. On the other hand, given a reference wind cycle, it is possible to obtain optimal devices (generator – reducer – DC bus) whose energy efficiency is nearly equivalent to the ones obtained with active and more complex systems with MPPT control. Based on a sensitivity analysis of performance versus parametric uncertainties, one major contribution deals with a design methodology integrating robustness issues inside the optimization process.; Ce travail présente une méthodologie de Conception Optimale Intégrée (COI) d'un système éolien entièrement passif pour offrir un compromis coût- fiabilité - performance très satisfaisant. En l'absence d'électronique de puissance et de contrôle par MPPT, le dispositif n'est efficace que si l'adaptation des constituants est optimale. L'extraction de vent ainsi que les pertes globales du système sont donc optimisées à l'aide d'un algorithme génétique multicritère pour augmenter l'efficacité énergétique et minimiser la masse pour un profil de vent donné. La globalité du système(turbine – génératrice – redresseur - stockage) a été modélisée pour parvenir aux résultats d'optimisation et à la réalisation d'un prototype correspondant à une solution particulière. Les résultats obtenus montrent, d'une part, la cohérence entre modèles et expérience. D'autre part, il est possible, pour un profil de vent donné, d'obtenir une configuration optimale de l'ensemble génératrice – pont redresseur présentant des caractéristiques analogues à celles d'architectures « actives » plus complexes, associées à des lois de contrôle par MPPT. Suite à une analyse de sensibilité des performances aux paramètres, une de nos contributions concerne une approche de conception intégrant les questions de robustesse au sein même du processus d'optimisation.

International audience; This work presents design and experimentation of a full passive wind turbine system without active electronic part(power and control). The efficiency of such device can be obtained only if the system design parameters are mutually adapted through an Integrated Optimal Design (IOD) method. This approach based on multiobjective optimization, aims at concurrently optimizing the wind power extraction and the global system losses for a given wind speed profile while reducing the weight of the wind turbine generator. It allows us to obtain the main characteristics (geometric and energetic features) of the optimal Permanent Magnet Synchronous Generator (PMSG) for the passive wind turbine. Finally, experiments on the PMSG prototype built from this work show a good agreement with theoretical predictions. This validates the design approach and confirms the effectiveness of such passive device.

The effectiveness of full passive Wind Turbine (WT) systems has been recently demonstrated. Such low cost structures without active control and with a minimum number of sensors can be efficient only if the system design parameters are mutually adapted through an integrated optimal design approach. Even if there is a good agreement between theoretical design models and an actual experimental prototype, it is relevant to evaluate the WT efficiency to design variable variations. Thus, this work is devoted more specifically to the sensitivity analysis of a passive WT system according to electrical variable variations of the Permanent Magnet Synchronous Generator. It also investigates the interest of a robust design approach for reducing the sensitivity of the WT efficiency to specific variable variations.

International audience; In this paper, the Integrated Optimal Design (IOD) approach for energetic system design is discussed. IOD aims at concurrently optimizing the architecture, the element sizing and the energy management in an energetic system. IOD leads to complex optimization problems (typically mixed variable problems with several constraints and multiple objectives) which can be solved with direct optimization methods. We illustrate the interest of this approach through the design of a hybrid environmentally friendly locomotive moved by four DC motors supplied by a diesel engine generator in association with electric storage elements (batteries and ultracapacitors).

International audience; In this paper, the design of a "low cost full passive structure" of wind turbine system without active electronic part (power and control) is investigated. The efficiency of such device can be obtained only if the design parameters are mutually adapted through an optimization design approach. For this purpose, sizing and simulating models are developed to characterize the behavior and the efficiency of the wind turbine system. A model simplification approach is presented, allowing the reduction of computational times and the investigation of multiple Pareto-optimal solutions with a multiobjective genetic algorithm. Results show that the optimized wind turbine configurations are capable of matching very closely the behavior of active wind turbine systems which operate at optimal wind powers by using a MPPT control device.

This paper explores the use of Multiobjective Genetic algorithms (MOGAs) for the Integrated Optimal Design (IOD) of complex heterogeneous power systems in electrical engineering. IOD consists in simultaneously optimizing architecture, structural characteristics,sizing of the constitutive elements and energy management in complex systems. An example of IOD is given in the paper through the case of a traction device for electric vehicles. It is shown that MOGAs lead on the one hand to the optimization of given objectives for performance improvement and on the other hand, provide a better understanding of system behavior through the analysis of Pareto-optimal solutions.

In this paper, system design methodologies for optimizing heterogenous power devices in electrical engineering are investigated. The concept of Integrated Optimal Design (IOD) is presented and a simplified but typical example is given. It consists in finding Pareto-optimal configurations for the motor drive of an electric vehicle. For that purpose, a geometric optimization method (i.e the Hooke and Jeeves minimization procedure) associated with an objective weighting sum and a Multiobjective Genetic Algorithm (i.e. the NSGA-II) are compared. Several performance issues are discussed such as the accuracy in the determination of Pareto-optimal configurations and the capability to well spread these solutions in the objective space.

International audience; In this paper, the authors report the development of a Systemic Optimization Process (SOP) devoted to a passive wind turbine system with electrochemical storage bank. Aim of the SOP is to find the optimal combination and sizing among sets of system components, that meets the desired system requirements with the lowest system owning cost. The passive wind system associated to the storage bank interacts with wind and load cycles (deterministic data). Sets of passive wind turbines are obtained through an Integrated Optimal Design (IOD) process. The system cost model is inspired from constructor data for the wind turbines and related to the battery cycles for the storage bank. An optimization problem is developed and performed using an exhaustive search. The optimization results are finally exposed and discussed

International audience; In this paper, the authors investigate a robust Integrated Optimal Design (IOD) devoted to a passive wind turbine system with electrochemical storage bank: this stand alone system is dedicated to rural electrification. The aim of the IOD is to find the optimal combination and sizing among a set of system components that fulfils system requirements with the lowest system Total Cost of Ownership (TCO). The passive wind system associated with the storage bank interacts with wind speed and load cycles. A set of passive wind turbines spread on a convenient power range (2 - 16 kW) are obtained through an IOD process at the device level detailed in previous papers. The system cost model is based on data sheets for the wind turbines and related to battery cycles for the storage bank. From the range of wind turbines, a "system level" optimization problem is stated and solved using an exhaustive search. The optimization results are finally exposed and discussed through a sensitivity analysis in order to extract the most robust solution versus environmental data variations among a set of good solutions.