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Identification des paramètres des batteries lithium-ion : une étude comparative de différents modèles et techniques d'optimisation pour la modélisation des batteries
No full textInternational audienceAccurate modeling of lithium-ion batteries is crucial for estimating performance metrics such as lifespan, aging, and state of charge, especially in high-demand sectors like aerospace and automotive. This paper presents a comparative study of optimization techniques for identifying parameters in an equivalent electrical model (2RC) of lithium-ion batteries. The study evaluates traditional, metaheuristic, and bioinspired methods using experimental data from four public datasets (NASA, CALCE, OXFORD, HNEI), totaling 15 batteries. The parameter identification process involves minimizing the error between measured and modeled voltage data using various optimization algorithms, including Least Squares, Particle Swarm Optimization (PSO), and Simulated Annealing. The results show that metaheuristic techniques like PSO outperform traditional methods in terms of accuracy (lower Mean Squared Error) while maintaining acceptable computational cost. Notably, PSO achieved the best accuracy with only a minor increase in execution time compared to Least Squares. The study confirms that advanced optimization techniques are better suited for handling the nonlinearity and complexity of battery models. These findings highlight the potential of integrating such methods into battery management systems (BMS) for more robust and reliable performance monitoring and control
50 ans de recherche en Ordonnancement - théorie et applications
No full textInternational audienceThis paper presents an overview of scheduling research done over the last half century. The main focus is on what is typically referred to as machine scheduling. The first section describes the general framework for machine scheduling models and introduces the notation. The second section discusses the basic deterministic machine scheduling models, including single machine, parallel machines, flow shops, job shops, and open shops. The third section describes more elaborate models, including multi-objective and multi-agent scheduling models, scheduling with controllable processing times, scheduling with rejection, just-in-time scheduling, scheduling with due date assignments, time-dependent scheduling, and scheduling with batching and setups. The two subsequent sections consider scheduling under uncertainty; section four goes into online and robust scheduling and section five covers stochastic scheduling models. The next section describes a variety of important scheduling applications, including applications in manufacturing, in services, and in information processing. The last section presents the main conclusions and discusses future research directions.Cet article présente un aperçu des recherches en ordonnancement menées au cours du dernier demi-siècle. L'accent est mis principalement sur ce que l'on appelle communément l'ordonnancement des machines. La première section décrit le cadre général des modèles d'ordonnancement des machines et introduit la notation. La deuxième section aborde les modèles d'ordonnancement déterministes de base, notamment les problèmes mono-machines, les problèmes à machines parallèles, et les problèmes d'atelier. La troisième section décrit des modèles plus élaborés, notamment les modèles d'ordonnancement multi-objectifs et multi-agents, l'ordonnancement avec temps de traitement contrôlables, l'ordonnancement avec rejet, l'ordonnancement juste-à-temps, l'ordonnancement avec attribution de dates d'échéance, l'ordonnancement dépendant du temps et l'ordonnancement avec traitement par lots et configurations. Les deux sections suivantes abordent l'ordonnancement en situation d'incertitude ; la quatrième section aborde l'ordonnancement en ligne et robuste, et la cinquième les modèles d'ordonnancement stochastique. La section suivante décrit diverses applications importantes de l'ordonnancement, notamment dans les secteurs de la fabrication, des services et du traitement de l'information. La dernière section présente les principales conclusions et aborde les orientations futures de la recherche
Vers un support d'aide à la décision centré-humain pour l'ordonnancement avec shifts
No full textInternational audienceThe production supervisor job is known to be highly stressful, requiring humans to react quickly to complex and unforeseen socio-organizational situations, often under high time and hierarchical pressure, where inappropriate reactions can have disastrous economic consequences. In such situations, decision support systems (DSS) can be providential to help decision-makers make the best of their decisions, provided that such systems meet the desired levels of usability, acceptability, and effectiveness. Focusing on a particular industrial use case, this paper presents the outcomes of a design process centered on human needs, that keeps supervisors at the heart of the decision-making. We detail the chosen DSS architecture, the essence of the decision problems faced by supervisors, as well as a constraint programming (CP) approach able to deal with them. The paper also shows how CP can be coupled with humancomputer interactions, and proposes an ecological serious game that enables to experimentally assess the usability, acceptability, and effectiveness of the DSS
Conception et réalisation d'un système de détection de chute avant impact au sol : IA embarquée et micro-actionneur pyrotechnique
No full textNational audienceThis multi-disciplinary research project presents a low-power, portable, on-board system for detecting pre-falls in the elderly, in order to protect them by deploying an airbag. The original detection system requires only a single triaxial accelerometer and uses gas-generating energetic composites. In operation, it is an on-board AI (CNN or SNN) that decides whether or not to initiate combustion of the energetic material to generate the gas. This work has demonstrated the feasibility of a lightweight, miniature on-board system (in place of gas cylinders) to protect elderly people from falls, while increasing comfort.Ce travail de recherche multidisciplinaire présente un système embarqué portable de faible puissance dédié à la détection de pré chute des personnes âgées afin de les protéger grâce au déploiement d'un airbag. L'originalité du système de détection ne requiert qu'un seul accéléromètre triaxial et utilise des composites énergétiques générateurs de gaz. Dans fonctionnement, c'est une IA embarquée (CNN ou SNN) qui décide d'initier ou pas la combustion du matériau énergétique pour générer le gaz. Ces travaux ont démontré la faisabilité d'un système embarqué léger et miniature (à la place des bouteilles de gaz) pour protéger les personnes âgées des chutes tout en augmentant ainsi le confort
Approach for experimental evaluation of automotive virtualization
No full textInternational audienceModern automotive systems extensively use software to implement vehicle functionalities, from comfort to driverassistance, thus requiring many dozens of microprocessors to support these tasks. As the number of hardware components increases, so does complexity, weight, cost and fuel consumption. To offset this problem, virtualization is being considered to consolidate multiple tasks into fewer microprocessors. However, the isolation and safety assurances provided by virtualization must first be verified, particularly when tasks of different criticality are consolidated on the same physical system. This paper proposes an experimental approach for the evaluation of an hypervisor in the automotive context, which includes realistic scenarios to evaluate the impact of a failure. An experiment is performed on a popular hypervisor and the results are described
Static vs. Dynamic Characterization of p-GaN HEMTs: Discrepancies in Electrical Characteristics and their Dependence on Bias History
No full textThis paper was presented at the EPE 2025 conference and was subsequently selected for publication in the special issue of Elsevier's PEDC journal. Therefore, only the abstract appears on the conference website.International audienceQuasi-static electrical characteristics of p-GaN HEMTs fluctuate with bias history. This study evidences that dynamic operation is fortunately highly reproducible without pre-conditioning. The original experimental setup highlights that quasi-static data alone is insufficient for modeling dynamic behavior, while allowing precise detection of discrepancies, enabling improved transient modeling
Direct Numerical Simulation of the combustion of an aluminium particle in a reacting oxidizing flow
No full textAbstract déposé à la Conférence ICMF (International Conference on Multiphase Flow), ayant lieu du 12/05/2025 au 17/05/2025 à Toulouse (France)International audienceA 3-dimensional Direct Numerical Simulations (DNS) of an isolated aluminum (Al) particle combustion in air is presented. The focus is placed on three elements: 1) developing an accurate and robust numerical scheme for understanding the physiochemical processes involved in the Al combustion, 2) quantifying the impact of sub-oxides condensation onto the burning droplet and subsequent heterogeneous surface reactions on the Al vaporization processes, and finally, 3) evaluating existing vaporization laws (burn rate) which are applicable to macroscopic combustion models
Using Machine Learning Potentials to describe collision cascades phenomena in Germanium
No full textInternational audienceUnderstanding how radiation in extreme environments, such as space or nuclear facilities, affects semiconductor behavior is crucial for advanced microelectronics technologies in these domains. Among semiconductors, germanium plays a pivotal role due to its unique electronic properties, but despite its importance, the response of germanium to radiation-induced damages remains an active area of research with unanswered questions. Part of the damages due to the penetration of an incident particle are due to non-ionizing effects such as collision cascades. By colliding with the atoms of the semiconductor's crystalline network the incident particle creates defects such as vacancies, interstitial atoms and clusters of defects known as Displacement Damage (DD). In the case of crystalline semiconductor, such DD can lead to modification of the band structure responsible for unexpected and undesired behaviors.To describe at the atomic scale the collision cascade and its induced damages, Molecular Dynamic (MD) is often used. Given the high energies of incident particle, which can reach hundreds of keV, large cells containing millions of atoms are needed to carry out the MD calculations. Such number of atoms restrains the use of ab initio methods, and interatomic potentials seem to be a good compromise to reproduce displacement cascades. However, while being fast enough to be used for these large calculations, such potentials exhibit important flaws for the simulation of collision cascades. As they are usually fitted on equilibrium properties they fail to reproduce correctly the non-equilibrium processes that are happening during a collision cascades where atoms' diffusion, local melting and extremely short distances are expected to happen. Machine Learning Interatomic Potential (MLIP) have appeared as a promising alternative to empirical interatomic potential providing near ab-initio accuracy at a fraction of the computational cost. This enables the calculation of key properties such as defect formation energies and migration barriers with high precision. Despite this, simulating millions of atoms over long time scales remains challenging. To address this we propose to use the MiLaDy package 1 , which integrates hybrid descriptors combining fast and cheap descriptors with slow and accurate ones allowing the user to tune the computational cost of the MLIP. A key factor in the success of a MLIP lies in the quality of the training database. In this matter Germanium is particularly challenging using Density Functional Theory as Generalized Gradient Approximation (GGA) functionals such as PBE 2 fail to correctly describe its band gap, and more computational expensive functional, such as range-separated hybrid HSE06 3 are needed to describe Ge's electronic structures, making it impractical to create a germanium database. In this work, we will be using a recently developed functional (PBE + α) 4 able to correctly describe Ge properties at the cost of GGAs. To date, despite Germanium importance in semiconductor technologies, relatively few studies have focused on developing a MLIP for this material, and, to the best of our knowledge, no research has yet applied this method to the study of collision cascades. This work aims to develop a MLIP for germanium based on a new GGA functional, which will enable the study of radiation-induced collision cascades at an ab initio level. The validity of the newly developed MLIP is tested against results obtained with interatomic potentials coupled with advanced corrections accounting for electronic effects 5,6 </p
Transparent conductive electrodes based on GaAs-metal deep sub-wavelength high contrast grating
No full textInternational audienceA highly transparent and conductive electrode formed of a GaAs-based monolithic high-contrastgrating combined with an array of metal nanowires (mMHCG) operating in the near-infrared rangeis presented. Designed for the transmission of selected TE or TM polarized light around the 940 nmwavelength, the fabricated mMHCG demonstrates a remarkable light transmittance level of 85%,surpassing the Fresnel threshold by 16%, which corresponds to a relative transmittance of 122%with respect to the transmission through plain GaAs-air interface. Additionally, these structuresexhibit low sheet resistance of 1.4 Ω/sq. We achieve this performanceby fabricating semiconductordeep subwavelength monolithic high-contrast gratings integrating metal stripes placed either in therecesses or on top of the etched semiconductor gratings. The high transmittance of polarised lightthrough the mMHCG is demonstrated for the first time in the near-infrared range thanks to lowquality factor resonance tunnelling the light through semiconductor stripes in the TE configurationand through the air slots between semiconductor stripes in the TM configuration. This work servesas conclusive evidence of mMHCG's extraordinary transparency and low sheet resistance, despitethe significant challenges in the near-infrared spectral range posed by high free carrier absorptionand the nanoscale precision required for mMHCG fabrication. This work demonstrates theextension of the mMHCG approach as an efficient transparent conductive electrode intooptoelectronic devices such as LEDs, vertical-cavity surface-emitting lasers (VCSELs), andphotodetector