In this paper we discuss the stable solvability of the inverse problem of parameter identification in a jump diffusion model. Therefore we introduce the forward operator of this inverse problem and analyze its properties. We show continuity of the forward operator and stability of the inverse problem provided that the domain is restricted in a specific manner such that techniques of compact sets can be exploited. Furthermore, we show that there is an asymptotical non-injectivity which causes instability problems whenever the jump intensity increases and the jump heights decay simultaneously.

In this note, we consider an inverse problem in a jump diffusion model. Using characteristic functions we prove the injectivity of the forward operator mapping the five parameters determining the model to the density function of the return distribution.

Finite element simulation of thermoplastic components is gaining importance as the companies aim to avoid overdesign of the components. Cost of the component can be minimized by using an adequate amount of material for its application. Life of the component, in a particular application, can be predicted as early as during its design phase with the help of computer simulations. To achieve reliable simulation results, an accurate material model which can predict the material behaviour is vital. Most material models consist of a number of material parameters that needs to be fed into them. These material parameters can be identified with the inputs from physical tests. The accuracy of the data extracted from the physical tests, however, remains the base for the aforementioned process. The report deals with the implementation of optical measurement technique such as Digital Image Correlation (DIC) in contrast with the conventional extensometers. A tensile test is conducted on a glass fibre reinforced thermoplastic specimen, according to ISO 527-2/1A, to extract the experimental data with the help of DIC technique. The material behavior is reproduced within a finite element analysis software package LS-DYNA, with the combination of elastoplastic model called *MAT_024 and stress state dependent damage and failure model called GISSMO. The tensile test is performed under quasi-static condition to rule out the strain rate dependency of the thermoplastic material. The mesh sensitivity of the damage model is taken into account with the element size regularization. The thesis concerns setting up a routine for material parameter identification of thermoplastics by full-field calibration (FFC) approach. Also, comparison of the strain field in the specimen, obtained through the newly set up routine against the regular non-FFC i.e. extensometer measurement routine. The major objective being, through the comparisons, a qualitative assessment of the two routines in terms of calibration time vs. gain in simulation accuracy. Material models obtained through both the routines are implemented in three-point and four-point bending simulations. The predicted material behaviors are evaluated against experimental tests.

No description available.

[pt] O crescente uso de veículos aéreos não tripulados (VANTs) em diversos setores da sociedade é fruto de avanços da tecnologia. Por sua vez, a ampliação de aplicações de VANTs traz consigo a necessidade de aumento de robustez destes sistemas, especialmente em ambientes compartilhados com o ser humano. A presente dissertação aborda o desenvolvimento de uma plataforma para testes de veículos multicópteros, com o objetivo de contribuir para o processo de desenvolvimento e implementação de drones, permitindo sua movimentação em torno dos seus graus de liberdade de rotação e realizando medições de atitude e força geradas pelo sistema, sem colocar o veículo ou seu operador em risco. Todos os dados adquiridos pela plataforma são transmitidos para um computador, onde foi desenvolvida uma interface virtual para sua visualização em tempo real, além de permitir armazenamento para pós-processamento e análises futuras. Também apresenta-se e discute-se o desenvolvimento do simulador de trajetórias proposto, que mostra o deslocamento do veículo em função da sequência de comandos fornecida, com base nos dados adquiridos pela plataforma. No intuito de se propiciar um melhor entendimento do funcionamento do sistema aqui desenvolvido, é apresentado um estudo detalhado dos subsistemas que compõem um multicóptero, bem como do processo de modelagem dinâmica de um veículo quadricóptero, por meio da técnica de grafos de ligação. A modelagem do veículo é complementada com a identificação de parâmetros fundamentais para a implementação do modelo, sendo discutidos métodos para identificação de parâmetros inerciais do veículo e parâmetros dinâmicos do sistema motopropulsor. / [en] The growing use of unmanned aerial vehicles (UAVs) in various sectors of society is a result of advances in technology. In turn, the expansion of UAV applications brings with it the need to increase the robustness of these systems, especially in environments shared with humans. and comes together with the need for increased robustness due to its use in shared environments with humans. This dissertation approaches the development of a platform for testing multicopter vehicles aiming at assisting the process of developing and implementing drones, allowing movements around their rotational degrees of freedom and making measurements of attitude and forces generated by the system, without putting the vehicle or its operator at risk. All data acquired by the platform is transmitted to a computer, where a virtual interface was developed to provide real time visualization, in addition to allowing data storage for post-processing and future analysis. The development of the proposed trajectory simulator is also presented and discussed, that shows the displacement of the vehicle as a function of the sequence of commands provided, based on the acquired data. Aiming at allowing a better understanding of the functioning of the developed system, a detailed study of the subsystems that compose a multicopter is presented, as well as the process of dynamic modeling of a quadcopter vehicle, by using bond graph technique. The modeling of the vehicle is complemented with the identification of fundamental parameters for the model implementation, such as methods for the identification of inertial parameters of the vehicle and dynamics of the powertrain system.

No description available.

Lithium-ion (Li-ion) batteries are amongst the most commonly used types in Electric (EVs) and Hybrid Electric (HEVs) Vehicles due to their high energy and power densities, as well as long lifetime. A battery is one of the most important components of an EV and hence it needs to be monitored and controlled accurately. The safety, and reliability of battery packs must then, be ensured by accurate management, control, and monitoring functions by using a Battery Management System (BMS). A BMS is also responsible for accurate real-time estimation of the State of Charge (SoC), State of Health (SoH) and State of Power (SoP) of the battery. The battery SoC provides information on the amount of energy left in the battery. The SoH determines the remaining capacity and health of a pack, and the SoP represents the maximum available power. These critical battery states cannot be directly measured. Therefore, they have to be inferred from measurable parameters such as the current delivered by the battery as well as its terminal voltage. Consequently, in order to offer accurate monitoring of SoC, SoH and SoP, advanced numerical estimation methods need to be deployed. In the estimation process, the states and parameters of a system are extracted from measurements. The objective is to reduce the estimation errors in the presence of uncertainties and noise under different operating conditions. This thesis uses and provides different enhancements to a robust estimation strategy referred to as the Smooth Variable Structure Filter (SVSF) for condition monitoring of batteries. The SVSF is a predictor-corrector method based on sliding mode control that enhances the robustness in the presence of noise and uncertainties. The methods are proposed to provide accurate estimates of the battery states of operation and can be implemented in real-time in BMS. To improve the performance of battery condition monitoring, a measurement-based SoC estimation method called coulomb counting is paired with model-based state estimation strategy. Important considerations in parameter and state estimation are model formulation and observability. In this research, a new model formulation that treats coulomb counting as an added measurement is proposed. It is shown that this formulation enhanced information extraction, leading to a more accurate state estimation, as well as an increase in the number of parameters and variables that can be estimated while maintaining observability. This model formulation is used for characterizing the battery in a range of operating conditions. In turn, the models are integral to a proposed adaptive filter that is a combination of the Interacting Multiple Model (IMM) concept and the SVSF. It is shown that this combined strategy is an efficient estimation approach that can effectively deal with battery aging. The proposed method provides accurate estimation for various SoH of a battery. Further to battery aging adaptation, measurement errors such as sensor noise, drift, and bias that affect estimation performance, are considered. To improve the accuracy of battery state estimation, a noise covariance adaptation scheme is developed for the SVSF method. This strategy further improves the robustness of the SVSF in the presence of unknown physical disturbances, noise, and initial conditions. The proposed estimation strategies are also considered for their implementation on battery packs. An important consideration in pack level battery management is cell-to-cell variations that impact battery safety. This study considers online battery parametrization to update the pack’s model over time and to detect cell-to-cell variability in parallel-connected battery cells configurations. Experimental data are used to validate and test the efficacy of the proposed methods in this thesis. / Thesis / Doctor of Philosophy (PhD) / To address the critical issue of climate change, it is necessary to replace fossil-fuel vehicles with battery-powered electric vehicles. Despite the benefits of electric vehicles, their popularity is still limited by the range anxiety and the cost determined by the battery pack. The range of an electric vehicle is determined by the amount of charge in its battery pack. This is comparable to the amount of gasoline in a gasoline vehicle’s tank. In consideration of the need for methods to address range anxiety, it is necessary to develop advanced algorithms for continuous monitoring and control of a battery pack to maximize its performance. However, the amount of charge and health of a battery pack cannot be measured directly and must be inferred from measurable variables including current, voltage and temperature. This research presents several algorithms for detecting the range and health of a battery pack under a variety of operating conditions. With a more accurate algorithm, a battery pack can be monitored closely, resulting in lower long-term costs. Adaptive methods for determining a battery’s state of charge and health in uncertain and noisy conditions have been developed to provide an accurate measure of available charge and capacity. Methods are then extended to improve the determination of state of charge and health for a battery module.

No description available.

Cette thèse a pour objectif le développement d'une stratégie d'identification des paramètres de plasticité et d'endommagement jusqu'à amorçage, pour des métaux ductiles.Un formalisme logarithmique est utilisé pour simuler les grandes déformations subies par les éprouvettes et une formulation non-locale multi-champ permet de simuler l'adoucissement indépendamment du maillage utilisé et d'éviter le verrouillage volumique.La Corrélation d'Images Digitales est utilisée pour obtenir des mesures hétérogènes plein champ à partir d'éprouvettes entaillées.La stratégie proposée s'appuie sur des observations microscopiques et sur une approche d'identification par recalage de modèle éléments finis (FEMU), visant à minimiser l'écart entre une mesure et son pendant simulé. L'écart est exprimé en termes de force et déplacement grâce à une normalisation appropriée. L'application de la FEMU est guidée par des analyses de sensibilité.La robustesse de la comparaison essai-calcul est assurée par l'application de conditions au bord mesurées. L'effet négatif de l’incertitude de mesure est mis en évidence et une solution de filtrage innovante est proposée.La stratégie est appliquée pour l'identification des paramètres de l'alliage Inconel625. Elle permet de reproduire l'amorçage pour des éprouvettes planes, en termes de réponse macroscopique et de localisation des sites d'amorçage. / This thesis proposes an identification strategy for plastic behaviour and damage up to the onset of fracture, for an application to ductile metals.A logarithmic finite strain formulation is used to simulate the large deformations undergone by the specimens, while a locking-free non-local formulation allows a mesh independent simulation of the softening behaviour.Digital Image Correlation is used to obtain heterogeneous full-field measurements from tensile tests on notched specimens.The identification strategy is based both on microscopic observations and on a Finite Element Model Updating (FEMU) technique, according to which the parameters are identified by minimizing the discrepancy between experiment and simulation. The discrepancy is quantified both in terms of displacement and force thanks to an appropriate normalization. The application of FEMU is guided using sensitivity analysis.The robustness of the comparison between simulation and measurement is ensured by prescribing measured displacements as boundary conditions for the simulation. The negative effect of the measurement uncertainty is underlined, and an innovative filtering approach is proposed.The proposed strategy is used to identify the materials' parameters of alloy Inconel625. It allows to reproduce the onset of fracture for flat specimens, both in terms of macroscopic response and crack initiation location.

Sistemas de levitação eletromagnética são de interesse quando se necessita de tecnologia envolvendo redução de atrito, atuação sem contato físico, máquinas rotativas e trens de alta velocidade. Devido à presença de não linearidades em sua dinâmica, pesquisadores têm dado atenção ao desenvolvimento de controladores mais sofisticados, com o objetivo de melhorar o desempenho desses sistemas. Controladores lineares apresentam limitações na faixa de operação da variável controlada e, geralmente apresentam baixa robustez quando aplicados em sistemas não lineares. O objetivo deste trabalho é desenvolver controladores não lineares com diferentes estruturas e analisá-los quando aplicados em um protótipo do sistema físico. Inicialmente, o sistema é modelado matematicamente através da abordagem fenomenológica. Em seguida, os parâmetros do modelo são identificados através de dados obtidos experimentalmente. Conhecendo bem a dinâmica do sistema através do modelo, são projetados três controladores de diferentes estruturas utilizando simulações computacionais. O primeiro é o PID clássico, controle linear amplamente utilizado em processos industriais. O segundo controlador é um PID com topologia não linear, denominado NPID. Este visa reduzir as limitações encontradas no PID linear, através de funções não lineares em seus termos. O último e mais complexo se trata do controle por modos deslizantes (SMC). Também com estrutura não linear, o SMC possui como característica intrínseca a robustez a variações da planta. Ao final, são realizadas simulações e os controladores avaliados são implementados de maneira digital em um hardware de controle e aplicados em uma planta piloto de levitação eletromagnética. Os resultados de desempenho obtidos permitem avaliar qual topologia de controlador melhor se enquadra diante dessa aplicação. / Electromagnetic levitation systems are of interest when it is necessary the use of technology involving reduction of friction, acting without physical contact, rotating machinery and high speed trains. Due to the nonlinear dynamics, researchers have paid attention to the development of more sophisticated controllers, in order to improve the performance of these systems. Linear controllers have limitations in the operating range of the controlled variable and generally have low robustness when applied to linear systems. The objective of this work is to develop nonlinear controllers with different structures and analyze them, when applied to a prototype of the physical system. Initially the system is modeled mathematically through the phenomenological approach. Then the model parameters are identified by experimentally obtained data. Knowing the dynamic of the system through the model, three different controllers are designed using computer simulations. The first is the classic PID, a linear control widely used in industrial processes. The second controller is a PID with nonlinear topology, called NPID. This controller is intended to reduce the limitations found in the linear PID through non linear functions on its terms. The last and most complex is the sliding mode control (SMC). Also a nonlinear structure, the SMC has the intrinsic characteristic of robustness to variations of the plant. In the end, the simulations are performed and the evaluated controllers are implemented in digital form in a hardware control and applied in a pilot plant of an electromagnetic levitation system. With the performance results it is possible to verify which controller topology best fits this application.