Depuis des siècles nous utilisons des véhicules équipés des systèmes de suspension de vibrations. Ils permettent d'avoir un confort acceptable et ajoutent de la sécurité à la conduite. Les nouveaux systèmes installés dans les véhicules sont des systèmes actifs. Ils peuvent être adaptés selon les exigences en temps réel. Ces types de systèmes sont utilisés pour l'amortissement de vibrations et pour l’isolation vibro-acoustique. Dans la thèse nous présentons une nouvelle approche d'un système adaptatif pour les applications automobiles. Nous faisons l'hypothèse qu’un portage d'un système centralisé en système distribué peut améliorer son efficacité. Nous proposons un réseau de capteurs sans fil pour l’amortissement de vibrations dans les applications automobiles. Un capteur du réseau est capable de mesurer des vibrations, d’amortir des vibrations et de récupérer l’énergie depuis les vibrations en utilisant un seul élément piézoélectrique (la méthode Serial-SSHI). Ensuite nous validons le réseau de capteurs sur une structure mécanique de type plaque. Les mesures sont comparées avec des simulations d’éléments finis. Les résultats des mesures et des simulations confirment le choix des solutions. Le nœud du réseau fournit ses fonctionnalités destinées avec une efficacité acceptable. Nous validons la récupération d’énergie depuis les vibrations et la mesure des vibrations. Ensuite nous validons un effet local d’amortissement de vibrations et un effet global (le réseau de capteurs permet d’avoir une action d’amortissement complémentaire). / For centuries we have used vehicles equipped with the vibration suspension systems. These systems are used to provide comfort and safety. Nowadays we are implementing the active systems which can be adapted according to the real-time requirements. These types of systems are used to damp vibrations and to provide noise and vibration insulation. In the thesis we present a new approach of an adaptive system for automotive applications. We assume that a porting of a centralized system in a distributed system can improve its effectiveness. We offer a wireless sensor network for damping vibration in automotive applications. A network sensor is able to measure the vibrations, damp the vibrations and energy harvesting from vibrations by using a single piezoelectric element (Serial-SSHI method). We validate the network of nodes on a mechanical structure. The measurements are compared with finite element simulations. The results of measurements and simulations confirm the choice of solutions. The network node provides designed functionality with acceptable efficiency. We also validate the energy harvesting and the vibration measurements. The outcome of the work confirm a local effect of vibrations damping and a global effect (the designed Wireless Sensor Network provides a supplementary damping action).

This thesis first presents a new cooperative wireless communication network strategy that incorporates energy cooperation and data cooperation. The model establishment, design goal formulations, and algorithms for throughput maximization of the proposed protocol are presented and illustrated using a three-node network with two energy harvesting (EH) user nodes and a destination node. Transmission models are established from the performance analysis for a total of four scenarios. Based on the models, we seek to find optimal energy management strategies by jointly optimizing time allocation for each user, power allocations over these time intervals, and data throughputs at user nodes so as to maximize the sum-throughput or, alternatively, the minimum throughput of the two users in all scenarios. An accelerated Newton barrier algorithm and an alternative algorithm based on local quadratic approximation of the transmission models are developed to solve the aforementioned optimization problems. Then the thesis extends the cooperative strategy to multi-source wireless communication network, where N source users communicate with the destination via one relay that harvests energy from the RF signals transmitted by the sources through time-division multiple access (TDMA). We characterize the Energy-Throughput (E-T) tradeoff regions between the maximum achievable average throughput of the sources and the total amount of saved energy in three circumstances. For the case N=1, all harvested energy will be used to forward the message. For the case N>1, we compare two transmission strategies: one is common PS ratio strategy that the relay adopts the same PS ratio for all sources; the other is individual PS ratio strategy that each source uses an individual PS ratio. Numerical experiments under practical settings provide supportive evidences to our performance analysis. / Graduate

Dans le domaine de l'Internet des Objets (IOT) les matériaux magnétoélectriques composites (MEC) trouvent leurs potentiels utilités dans la récupération d'énergie de microsystèmes autonomes. L'aspect géométrique des matériaux MEC se traduit par l'assemblage de matériaux piézoélectriques et magnétostrictifs sous formes laminaires ou sous formes de mixture par grains. Dans tous les cas ces matériaux possèdent, sous certaines conditions, des coefficients magnétoélectriques qui peuvent fournir des tensions et des puissantes suffisantes pour alimenter des microsystèmes autonomes. Mes travaux de recherche ont porté essentiellement sur une contribution à la modélisation de ces matériaux MEC à l'aide de méthodes analytiques et d'un code numérique basé sur la méthode des éléments finis (MEF) en 2D. Une méthode basée sur la combinaison du tenseur de Maxwell avec le model de Jiles-Atherton modifié a été proposée pour inclure dans la MEF la non-linéarité des couches magnétostrictives. Une étude sur les performances des structures multicouches a été réalisée afin de déterminer la configuration optimale pour les matériaux élaborés à base de couches minces. Une potentielle application dans le domaine biomédical est finalement présentée afin de prouver l'efficience d'un transducteur d'énergie MEC dans ce domaine. Une série de mesures sur un composite bilame est présentée à la fin afin de montrer le plein accord avec la partie modélisation réalisée. / Currently, the "Internet of Everything" (IoE) technologies have attracted significant researchers in the international scientific community. The IoE is based on the idea that identifiable objects are located and controlled via the Internet. To achieve this goal, it is necessary to design embedded systems in millimeter/micrometer scales composed of wireless sensor nodes while overcoming a major drawback of the excessive use of batteries which are limited in lifetime and yield pollutants. The problem calls for the supply of green energy harvesting for wireless sensors. To utilize mechanical vibrations and electromagnetic energy more efficiently, it would be necessary to get simultaneously both energies using materials sensitive to the electromagnetic field and the mechanical vibration such as magnetoelectric materials (ME) that combine the magnetostrictive and piezoelectric effects. Experimental results of ME coefficients from the fabricated ME composites have confirmed the possibility to obtain a few of V/(cm∙Oe) in no-resonant regime and few tens of V/(cm∙Oe) in resonant regime. In case of classical laminate bulk material (Terfenol-D/PZT/Terfenol-D), the delivered powers into optimal impedance are in the order of mW/ cm3. Thus in this context the research work in this thesis focuses on the establishment and assessment of the modelling approaches. The contribution includes analytical numerical methods and a 2D multiphysics finite element method to estimate the performance of the ME materials according to different polarizations and parameters.

Energy harvesting system is a system which could convert ambient energy into electrical power, its output depends on the energy availability of ambient conditions. For indoor condition, light is a typical available energy, and solar panel could be used to harvest it. To determine the light energy availability of an unknown condition, normally, a lot of measurements is needed, and it will cost a long time. This paper introduced a whole design process of a simulation system, it used modelling method to estimate the energy availability of unknown light condition, and this method is more quickly. A matched measurement system for solar panel and environmental parameters was built firstly. Then, all these environmental parameters were analyzed to find out their influence on solar panel. These parameters, which have relation to the output of the solar panel were thought as influence factors and used for model and classifier building. To get an accurate simulation result, different modeling and classification methods were compared and some suggested methods were picked out. Comparing the simulation result with the real output measurement, the method with minimum error was accepted in the final system. A user interface was built in the end to make this system become more user-friendly. This system could be used to simulate the energy availability of a new condition and analyze the error of simulation results which generated by different methods.

Since the wireless sensor network has appeared, it plays an important role in human life. It has the ability to help people automatically sense the real world, where is inaccessible before. Although the applications of wireless sensor networks are increasing nowadays, one of the great issues facing sensor network is the lifetime of a system. Since the system relies on the limited battery, finite lifetime is its biggest challenge. Fortunately, solar energy harvesting for the outdoor environment is promised to address that problem. Compared with that, indoor energy harvesting is still an immature field for most applications, since it is complex to estimate the available energy for indoor lights. To complement the vacancy of indoor energy harvesting field, improve the performance of the traditional estimation model, a new solar cell model is proposed to substitute the traditional solar cell model. The traditional estimation model is used to roughly dimension the indoor system, regardless of the different impact generated by different light sources. The new estimation model, was established under the real indoor environmental conditions. A classification model is created to distinguish the sort of the light sources. The single solar cell of the traditional model is replaced by 5 different solar cell models fitted for each kind of light source. With that, the system has the ability to select the most suitable solar cell model based on the classification result. Moreover, a verification model was built to evaluate both estimation models. The evaluation result shows that the new model has the ability to perform well under changing light condition.

Thermoelectric generators (TEG) directly convert heat energy into electrical energy. The impediments as to why this technology has not yet found extensive application are the low conversion efficiency and high costs per watt. On the one hand, the manufacturing process is a cost factor. On the other, the high-­‐priced thermoelectric (TE) materials have an enormous impact on the costs per watt. In this thesis both factors will be examined: the production process and the selection of TE materials. Technical screen printing is a possible way of production, because this method is very versatile with respect to the usable materials, substrates as well as printing inks. The organic conductor PEDOT:PSS offers reasonable thermoelectric properties and can be processed very well in screen printing. It was demonstrated by prototypes of fully printed TEGs that so-­‐called vertical printed TEGs are feasible using standard graphic arts industry processes. In addition, the problems that occur with print production of TEGs are identified. Finally, approaches to solve these problems are discussed.

Les progrès technologiques accomplis durant ces dernières décennies dans les domaines des microsystèmes et des radiocommunications nous permettent de réaliser des composants communicants miniaturisés à faible coût afin de constituer des réseaux de capteurs sans fil. Typiquement, chacun de ces composants intègre une ou plusieurs unités de mesures (capteur), une unité de traitement de données, une unité de communication radio et une batterie. De ce fait, un nouveau domaine de recherche s’est créé pour étudier le déploiement de ces réseaux afin d’offrir des solutions de surveillance et de contrôle à distance, notamment dans des environnements complexes ou inaccessibles. Les domaines d’application de ces capteurs sont très variés, allant de la domotique au militaire en passant par le médical et les infrastructures civiles. Souvent, ces applications impliquent des contraintes sévères en terme d’autonomie qui idéalement devrait atteindre plusieurs dizaines d’années. Pour atteindre cet objectif, il est à la fois nécessaire de réduire la consommation énergétique du nœud capteur et de trouver d’autres solutions d’alimentation en énergie pour le nœud. Pour adresser ce deuxième point, la récupération d’énergie à partir de l’environnement (solaire, vibratoire, thermique, etc.) semble représenter une solution idéale pour alimenter un nœud capteur, bien que celui-ci doive s’adapter aux faibles quantités d’énergie récupérées par ces systèmes, ainsi qu’à leurs variations et intermittences. Ces travaux de thèse s’intéressent donc à la problématique de la simulation et de la réduction de la consommation des nœuds de capteurs sans-fil et autonomes en énergie. Dans un premier temps, nous avons développé la plateforme HarvWSNet, un environnement de co-simulation alliant le simulateur de réseaux WSNet et Matlab permettant ainsi la modélisation précise et la simulation hétérogène des protocoles de communication (typiquement à événements discrets) et des systèmes de récupération d’énergie (qui possèdent typiquement un comportement à temps continu). Nous avons démontré que cette plateforme permet de réaliser très rapidement des études de pré-prototypage de scénarios applicatifs de déploiement et ainsi réduire le temps de conception de ces nouvelles technologies. Grâce à la modélisation précise des éléments du système de récupération d’énergie (batterie, supercapacité, etc.) permise par cette plateforme, nous avons étudié et évalué la durée de vie de déploiements à large échelle de réseaux de capteurs alimentés par des systèmes de récupération d’énergie (solaire et éolien). La deuxième contribution de cette thèse concerne l’étude et l’implémentation de stratégies de reconfiguration dans l’interface de communication radio, qui est souvent la principale source de consommation d’énergie d’un capteur, afin de permettre au nœud et/ou au réseau de minimiser sa consommation lorsque le bilan de liaison RF est favorable. A cette fin, nous avons proposé une approche originale grâce au développement d’un simulateur de réseau dédié, EnvAdapt (basé sur WSNet). Dans cette nouvelle plateforme, des modèles de consommation des différents blocs du transceiver radio et des algorithmes de reconfiguration ont été implémentés afin d’étudier l’impact de la reconfiguration des performances de la radio sur la qualité de service et l’autonomie d’un réseau de capteurs. / Technological advances achieved over the past decade in the fields of microsystems and wireless communications have enabled the development of small size and low cost sensor nodes equipped with wireless communication capabilities able to establish a wireless sensor network (WSN). Each sensor node is typically equipped with one or several sensing unit, a data processing unit, a wireless communication interface and a battery. The challenges raised by WSNs has lead to the emergence of a new research domain which focuses on the study and deployment of such a networks in order to offer the required remote monitoring and control solutions for complex and unreachable environment. WSNs have found application in a wide range of different domains, including home and structural health monitoring, military surveillance, and biomedical health monitoring. These applications usually impose stringent constraints on the WSN lifetime which is expected to last several years. To reach this objective, it is necessary to reduce the overall energy consumption of the sensor node and to find an additional source of energy as well. To address the last point, energy harvesting from the environment seems to be a an efficient approach to sustain WSNs operations. However, energy harvesting devices, which must also be small, are usually unable to ensure a continuous operation of sensor nodes. Thus, it is necessary to adapt the WSN consumption and activity to the low and unpredictable energy scavenged. The work presented in this thesis focuses on the issue of simulation and power consumption of autonomous sensor nodes. We have first developed, HarvWSNet, a co-simulation framework combining WSNet and Matlab that provides adequate tools to accurately simulate heterogenous protocols (based on discrete-time events) and energy harvesting systems (based on continuous-time events). We have demonstrated that HarvWSNet allows a rapid evaluation of energy-harvesting WSNs deployment scenarios that may accelerate the time-to-market for these systems. Thanks to the accurate energy models (battery, supercapacitor, etc.) implemented in this platform, we have studied and evaluated a large scale deployment of solar and wind energy-harvesting WSNs. Our second contribution focuses on the implementation of energy-aware reconfiguration strategies in the radio transceiver which is usually considered as the most energy hungry component in a sensor node. These strategies are intended to reduce the excessive power consumption of the radio transceiver when the channel conditions are favorable. To this end, we have a new simulation framework called EnvAdapt (based also on WSNet) dedicated to the evaluation of reconfigurable radio transceivers for WSNs. In EnvAdapt, we have implemented the required radio transceiver behavioral and power consumption models that allows the evaluation of the impact of radio transceiver reconfiguration on the communication performance and lifetime of WSNs.

Energy harvesting using piezoelectric nanomaterials provides an opportunity for advancement towards self-powered systems. Self-powered systems are a new emerging technology, which allows the use of a system or a device that perform a function without the need for external power source like for example, a battery or any other type of source. This technology can for example use harvested energy from sources around us such as ambient mechanical vibrations, noise, and human movement, etc. and convert it to electric energy using the piezoelectric effect. For nanoscale devices, the size of traditional batteries is not suitable and will lead to loss of the concept of “nano”. This is due to the large size and the relatively large magnitude of the delivered power from traditional sources. The development of a nanogenerator (NG) to convert energy from the environment into electric energy would facilitate the development of some self-powered systems relying on nano- devices. The main objective of this thesis is to fabricate a piezoelectric Zinc Oxide (ZnO) NGs for low frequency (˂ 100 Hz) energy harvesting applications. For that, different types of NGs based on ZnO nanostructures have been carefully developed, and studied for testing under different kinds of low frequency mechanical deformations. Well aligned ZnO nanowires (NWs) possessing high piezoelectric coefficient were synthesized on flexible substrates using the low temperature hydrothermal route. These ZnO NWs were then used in different configurations to demonstrate different low frequency energy harvesting devices. Using piezoelectric ZnO NWs, we started with the fabrication of sandwiched NG for hand writing enabled energy harvesting device based on a thin silver layer coated paper substrate. Such device configurations can be used for the development of electronic programmable smart paper. Further, we developed this NG to work as a triggered sensor for wireless system using foot-step pressure. These studies demonstrate the feasibility of using ZnO NWs piezoelectric NG as a low-frequency self-powered sensor, with potential applications in wireless sensor networks. After that, we investigated and fabricated a sensor on PEDOT: PSS plastic substrate either by one side growth technique or by using double sided growth. For the first growth technique, the fabricated NG has been used as a sensor for acceleration system; while the fabricated NG by the second technique has worked as anisotropic directional sensor. This fabricated configurations showed stability for sensing and can be used in surveillance, security, and auto-mobil applications. In addition to that, we investigated the fabrication of a sandwiched NG on plastic substrates. Finally, we demonstrated that doping ZnO NWs with extrinsic element (such as Ag) will lead to the reduction of the piezoelectric effect due to the loss of crystal symmetry. A brief summary into future opportunities and challenges are also presented in the last chapter of this thesis.

Structural Health Monitoring (SHM) systems were developed to evaluate the integrity of a system during operation, and to quickly identify the maintenance problems. They will be used in future aerospace vehicles to improve safety, reduce cost and minimize the maintenance time of a system. Many SHM systems were already developed to evaluate the integrity of plates and used in marine structures. Their implementation in manufacturing processes is still expected. The application of SHM methods for complex geometries and welds are two important challenges in this area of research. This research work started by studying the characteristics of piezoelectric actuators, and a small energy harvester was designed. The output voltages at different frequencies of vibration were acquired to determine the nonlinear characteristics of the piezoelectric stripe actuators. The frequency response was evaluated experimentally. AA battery size energy harvesting devices were developed by using these actuators. When the round and square cross section devices were excited at 50 Hz frequency, they generated 16 V and 25 V respectively. The Surface Response to Excitation (SuRE) and Lamb wave methods were used to estimate the condition of parts with complex geometries. Cutting tools and welded plates were considered. Both approaches used piezoelectric elements that were attached to the surfaces of considered parts. The variation of the magnitude of the frequency response was evaluated when the SuRE method was used. The sum of the square of the differences was calculated. The envelope of the received signal was used for the analysis of wave propagation. Bi-orthogonal wavelet (Binlet) analysis was also used for the evaluation of the data obtained during Lamb wave technique. Both the Lamb wave and SuRE approaches along with the three methods for data analysis worked effectively to detect increasing tool wear. Similarly, they detected defects on the plate, on the weld, and on a separate plate without any sensor as long as it was welded to the test plate.

La technologie de réseau cellulaire de 5ème génération (5G) sera le réseau supportant l'Internet des objets (IoT). Elle a introduit une fonctionnalité majeure, communications appareil-à-appareil (D2D), que permettent communications sans fil à consommation d'énergie restreinte en interagissant à proximité et à puissance d'émission plus faible. La coopération entre appareils suscit donc un intérêt considérable pour l'énergie, et peut être utilisé en conjonction avec la récupération d'énergie pour prolonger la durée de vie des appareils. Les programmes de coopération renforcent la mise en réseau d'un appareil à l'autre, ce qui accroît la nécessité d'exécuter des mécanismes de sécurité pour assurer la protection des données et les relations de confiance entre les nœuds du réseau.Ces mécanismes sont fondamentaux pour la protection contre les attaques malveillantes mais elles représentent aussi une importante consommation d'énergie, souvent négligée en raison de l'importance de la protection des données. L'établissement d'un canal securisé peut être coûteux en termes d'utilisation du CPU, la mémoire et la consommation d'énergie, surtout si les appareils sont limités en ressources. La confidentialité et l’intégrité des données ont un faible coût énergétique, mais sont utilisées en permanence. Il est donc nécessaire de quantifier la consommation d'énergie engendrée par la sécurité d'un appareil. Un modèle énergétique basé sur la sécurité est proposé pour répondre à cet objectif.Dans les réseaux composés d'équipements d'utilisateurs (UE), la mobilité est une caractéristique clé. Elle peut agir sur la connexion à proximité d'objets IoT, étendant la couverture 5G vers l'IoT via les UEs. Une solution d'authentification légère est présentée qui permet par l'authentification directe et des communications UE-IoT, d'étendre la couverture et réaliser des économies d'énergie potentielles importantes. Cette approche peut être particulièrement utile en cas de catastrophe où l'infrastructure réseau peut ne pas être disponible.La condentialité et l'authentification des données sont une source de consommation d'énergie importante. Les appareils équipés avec équipements de collecte d'énergie (EH) peuvent avoir un excédent ou un déficit d'énergie. La sécurité appliquée peut donc être ajustée en fonction de l'énergie disponible d'un appareil, en introduisant l'établissement de canal sécurisé qui tient compte de la consommation d'énergie. Après avoir étudié en profondeur les normes 5G, il a été constaté que les réseaux d'UE D2D utilisant ce type de norme dépenseraient une quantité importante d'énergie et seraient généralement moins sûr. Un mécanisme léger de recléage est donc proposé pour réduire les coûts liés cette adaptation. Pour compléter le concept de canal sécurisé prenant en compte l'énergie et le mécanisme de recléage, une méthode de bootstrapping des paramètres de sécurité est également présentée. Le méthode désigne le cœur du réseau (CN) comme responsable de la politique de sécurité, rend l'ensemble du réseau plus sûr et aide à prévenir les pannes de communication. L'adaptation susvisé requiert l'étude du compromis entre l’énergie et sécurité. À cette fin, un processus décisionnel de Markov (MDP) modélisant un canal de communication est présenté lorsqu'un agent choisit les éléments de sécurité à appliquer aux paquets transmis. Ce problème d'optimisation du contrôle stochastique est résolu par plusieurs algorithmes de programmation dynamique et d’apprentissage par le renforcement (RL). Les résultats montrent que l'adaptation susvisé peut prolonger de manière significative la durée de vie de l'équipement et de la batterie, et améliore la fiabilité des données tout en offrant des fonctions de sécurité. Une étude comparative est présentée pour les différents algorithmes RL. Puis une approche d'apprentissage Q-profond (DQL) est proposé que améliore la vitesse d'apprentissage de l'agent et la fiabilité des données. / The 5th Generation Cellular Network Technology (5G) will be the network supporting the Internet of Things (IoT) and it introduced a major feature, Device-to-Device (D2D) communications. D2D allows energy-constrained wireless devices to save energy by interacting in proximity at a lower transmission power. Cooperation and device-assisted networking therefore raise signicant interest with respect to energy saving, and can be used in conjunction with energy harvesting to prolong the lifetime of battery-powered devices. However, cooperation schemes increase networking between devices, increasing the need for security mechanisms to be executed to assure data protection and trust relations between network nodes. This leads to the use of cryptographic primitives and security mechanisms with a much higher frequency.Security mechanisms are fundamental for protection against malicious actions but they also represent an important source of energy consumption, often neglected due to the importance of data protection. Authentication procedures for secure channel establishment can be computationally and energetically expensive, especially if the devices are resource constrained. Security features such as condentiality and data authentication have a low energetic cost but are used constantly in a device engaged in data exchanges. It is therefore necessary to properly quantify the energy consumption due to security in a device. A security based energy model is proposed to achieve this goal.In User Equipment (UE) D2D networks, mobility is a key characteristic. It can be explored for connecting directly in proximity with IoT objects. A lightweight authentication solution is presented that allows direct UE-IoT communications, extending coverage and potentially saving signicant energy amounts. This approach can be particularly useful in Public Protection and Disaster Relief (PPDR) scenarios where the network infrastructure may not be available.Security features such as condentiality or data authentication are a significant source of consumption. Devices equipped with Energy Harvesting (EH) hardware can have a surplus or a deficit of energy. The applied security can therefore be adjusted to the available energy of a device, introducing an energy aware secure channel. After in depth analysis of 5G standards, it was found that D2D UE networks using this type of channel would spend a signicant amount of energy and be generally less secure. A lightweight rekeying mechanism is therefore proposed to reduce the security overhead of adapting security to energy. To complete the proposed rekeying mechanism, a security parameter bootstrapping method is also presented. The method denes the Core Network (CN) as the security policy maker, makes the overall network more secure and helps preventing communication outages.Adapting security features to energy levels raises the need for the study of the energy/security tradeoff. To this goal, an Markov Decision Process (MDP) modeling a communication channel is presented where an agent chooses the security features to apply to transmitted packets. This stochastic control optimization problem is solved via several dynamic programming and Reinforcement Learning (RL) algorithms. Results show that adapting security features to the available energy can signicantly prolong battery lifetime, improve data reliability while still providing security features. A comparative study is also presented for the different RL learning algorithms. Then a Deep Q-Learning (DQL) approach is presented and tested to improve the learning speed of the agent. Results confirm the faster learning speed. The approach is then tested under difficult EH hardware stability. Results show robust learning properties and excellent security decision making from the agent with a direct impact on data reliability. Finally, a memory footprint comparison is made to demonstrate the feasibility of the presented system even on resource constrained devices.