In recent years, the decrease of electronic components consumption has led to the development of wireless devices. An interesting application concerns Internet of Things (IoT) and Wireless Sensor Networks (WSNs). Sensors are used in various scenarios such as intelligent monitoring systems for office, home automation, medical or military applications. Today these sensors are powered by batteries. Despite significant progress, batteries still have a limited lifetime and their replacement is often complicated. This explains the motivation to find alternative ways to power these objects. A promising method consists in harvesting energy from the ambient environment of the sensor nodes. For instance, thermal gradients, mechanical vibrations, light or electromagnetic waves could serve such a purpose. This thesis has been funded by PRACOM and has been held in this context. The thesis aim is to contribute to the development of innovative solutions to design self-powered sensor networks particularly by exploiting the energy of Radio Frequency (RF) waves. These sensors are located in ambient environment, i.e. an environment for which the RF power densities are not controlled and generally low. First of all, different sources and energy harvesting techniques have been investigated. This study helps to position the RF energy harvesting to other systems such as the mechanical, thermal, chemical, photovoltaic energy. After having demonstrated the added value of harvesting energy over a wide frequency band, a statistical study has been conducted to evaluate the RF power density in urban environment and countryside. The sensor environment involves choices for the chosen architecture, such as the addition of an energy storage cell or the use of a dc-dc converter. Several multi-band RF harvesters have been designed and tested in various environments. They show the feasibility of powering small sensors. The issue of autonomous sensors worn by the person is also addressed. The study highlights how the presence of the human body has ...
In recent years, the decrease of electronic components consumption has led to the development of wireless devices. An interesting application concerns Internet of Things (IoT) and Wireless Sensor Networks (WSNs). Sensors are used in various scenarios such as intelligent monitoring systems for office, home automation, medical or military applications. Today these sensors are powered by batteries. Despite significant progress, batteries still have a limited lifetime and their replacement is often complicated. This explains the motivation to find alternative ways to power these objects. A promising method consists in harvesting energy from the ambient environment of the sensor nodes. For instance, thermal gradients, mechanical vibrations, light or electromagnetic waves could serve such a purpose. This thesis has been funded by PRACOM and has been held in this context. The thesis aim is to contribute to the development of innovative solutions to design self-powered sensor networks particularly by exploiting the energy of Radio Frequency (RF) waves. These sensors are located in ambient environment, i.e. an environment for which the RF power densities are not controlled and generally low. First of all, different sources and energy harvesting techniques have been investigated. This study helps to position the RF energy harvesting to other systems such as the mechanical, thermal, chemical, photovoltaic energy. After having demonstrated the added value of harvesting energy over a wide frequency band, a statistical study has been conducted to evaluate the RF power density in urban environment and countryside. The sensor environment involves choices for the chosen architecture, such as the addition of an energy storage cell or the use of a dc-dc converter. Several multi-band RF harvesters have been designed and tested in various environments. They show the feasibility of powering small sensors. The issue of autonomous sensors worn by the person is also addressed. The study highlights how the presence of the human body has an impact on RF harvester performance. Several solutions are proposed such as the improvement of the impedance matching network or the use of a high impedance surface. ; Les réseaux de capteurs sans fil (WSN: Wireless Sensor Network), l'Internet des objets (IOT), profitent des progrès récents en terme de consommation énergétique pour concevoir des entités de contrôle intelligentes. Les batteries ou piles ont permis le développement de ces systèmes en les rendant autonomes. Néanmoins, cette méthode d'alimentation est inadaptée pour les applications modernes. Une solution alternative pour alimenter ces capteurs est d'utiliser l'énergie disponible dans leur environnement, comme par exemple les gradients thermiques, les vibrations mécaniques, ou encore les ondes lumineuses ou Radio-Fréquences. C'est dans ce contexte que s'est déroulé ce travail de thèse financé par PRACOM. Cette thèse propose de contribuer au developpement de solutions innovantes visant à rendre autonome en énergie un réseau de capteurs en exploitant notamment l'énergie des ondes Radio-Fréquences (RF). Ces capteurs sont placés en environnement ambiant, c'est-à-dire dans un environnement pour lequel les densités de puissances incidentes ne sont pas maîtrisées et sont généralement faibles. Tout d'abord différentes sources et techniques de récupération d'énergie ont été étudiées comme l'énergie mécanique, thermique, chimique et celle des ondes lumineuses et Radio-Fréquences. Cette étude a permis de positionner les systèmes de récupération d'énergie des ondes Radio Fréquences par rapport aux autres systèmes. Après avoir démontré l'intérêt de collecter l'énergie sur une large bande de fréquence, une étude statistique a été menée sur l'évaluation de la densité de puissance RF présente dans un environnement urbain et à la campagne. L'environnement du capteur implique des choix pour l'architecture choisie, comme par exemple l'ajout de cellule de stockage d'énergie ou encore l'utilisation d'un convertisseur dc-dc. Plusieurs récupérateurs d'énergie RF multibandes ont été conçus et testés dans divers environnements. Ceux-ci montrent la faisabilité d'alimenter des petits capteurs en extérieur. La problématique des capteurs autonomes en énergie portés par la personne est également abordée. Il s'agit de voir comment la présence du corps humain a un retentissement sur les performances du système de récupération d'énergie RF. Plusieurs solutions sont proposées comme l'amélioration du réseau d'adaptation d'impédances du récupérateur d'énergie RF, ou encore l'utilisation d'une surface à hautes impédances.
In recent years, the decrease of electronic components consumption has led to the development of wireless devices. An interesting application concerns Internet of Things (IoT) and Wireless Sensor Networks (WSNs). Sensors are used in various scenarios such as intelligent monitoring systems for office, home automation, medical or military applications. Today these sensors are powered by batteries. Despite significant progress, batteries still have a limited lifetime and their replacement is often complicated. This explains the motivation to find alternative ways to power these objects. A promising method consists in harvesting energy from the ambient environment of the sensor nodes. For instance, thermal gradients, mechanical vibrations, light or electromagnetic waves could serve such a purpose. This thesis has been funded by PRACOM and has been held in this context. The thesis aim is to contribute to the development of innovative solutions to design self-powered sensor networks particularly by exploiting the energy of Radio Frequency (RF) waves. These sensors are located in ambient environment, i.e. an environment for which the RF power densities are not controlled and generally low. First of all, different sources and energy harvesting techniques have been investigated. This study helps to position the RF energy harvesting to other systems such as the mechanical, thermal, chemical, photovoltaic energy. After having demonstrated the added value of harvesting energy over a wide frequency band, a statistical study has been conducted to evaluate the RF power density in urban environment and countryside. The sensor environment involves choices for the chosen architecture, such as the addition of an energy storage cell or the use of a dc-dc converter. Several multi-band RF harvesters have been designed and tested in various environments. They show the feasibility of powering small sensors. The issue of autonomous sensors worn by the person is also addressed. The study highlights how the presence of the human body has ...
