Development of MEMS Piezoelectric Vibration Energy Harvesters with Wafer-Level Integrated Tungsten Proof-Mass for Ultra Low Power Autonomous Wireless Sensors

La génération d’énergie localisée et à petite échelle, par transformation de l’énergie vibratoire disponible dans l’environnement, est une solution attrayante pour améliorer l’autonomie de certains noeuds de capteurs sans-fil pour l’Internet des objets (IoT). Grâce à des microdispositifs inertiels résonants piézoélectriques, il est possible de transformer l’énergie mécanique en électricité. Cette thèse présente une étude exhaustive de cette technologie et propose un procédé pour fabriquer des microgénérateurs MEMS offrant des performances surpassant l’état de l’art. On présente d’abord une revue complète des limites physiques et technologiques pour identifier le meilleur chemin d’amélioration. En évaluant les approches proposées dans la littérature (géométrie, architecture, matériaux, circuits, etc.), nous suggérons des métriques pour comparer l’état de l’art. Ces analyses démontrent que la limite fondamentale est l’énergie absorbée par le dispositif, car plusieurs des solutions existantes répondent déjà aux autres limites. Pour un générateur linéaire résonant, l’absorption d’énergie dépend donc des vibrations disponibles, mais aussi de la masse du dispositif et de son facteur de qualité. Pour orienter la conception de prototypes, nous avons réalisé une étude sur le potentiel des capteurs autonomes dans une automobile. Nous avons évalué une liste des capteurs présents sur un véhicule pour leur compatibilité avec cette technologie. Nos mesures de vibrations sur un véhicule en marche aux emplacements retenus révèlent que l’énergie disponible pour un dispositif linéaire résonant MEMS se situe entre 30 à 150 Hz. Celui-ci pourrait produire autour de 1 à 10 μW par gramme. Pour limiter la taille d’un générateur MEMS pouvant produire 10 μW, il faut une densité supérieure à celle du silicium, ce qui motive l’intégration du tungstène. L’effet du tungstène sur la sensibilité du dispositif est évident, mais nous démontrons également que l’usage de ce matériau permet de réduire l’impact de l’amortissement fluidique sur le facteur de qualité mécanique Qm. En fait, lorsque l’amortissement fluidique domine, ce changement peut améliorer Qm d’un ordre de grandeur, passant de 103 à 104 dans l’air ambiant. Par conséquent, le rendement du dispositif est amélioré sans utiliser un boîtier sous vide. Nous proposons ensuite un procédé de fabrication qui intègre au niveau de la tranche des masses de tungstène de 500 μm d’épais. Ce procédé utilise des approches de collage de tranches et de gravure humide du métal en deux étapes. Nous présentons chaque bloc de fabrication réalisé pour démontrer la faisabilité du procédé, lequel a permis de fabriquer plusieurs prototypes. Ces dispositifs ont été testés en laboratoire, certains démontrant des performances records en terme de densité de puissance normalisée. Notre meilleur design se démarque par une métrique de 2.5 mW-s-1/(mm3(m/s2)2), soit le meilleur résultat répertorié dans l’état de l’art. Avec un volume de 3.5 mm3, il opère à 552.7 Hz et produit 2.7 μW à 1.6 V RMS à partir d’une accélération de 1 m/s2. Ces résultats démontrent que l’intégration du tungstène dans les microgénérateurs MEMS est très avantageuse et permet de s’approcher davantage des requis des applications réelles.Small scale and localized power generation, using vibration energy harvesting, is considered as an attractive solution to enhance the autonomy of some wireless sensor nodes used in the Internet of Things (IoT). Conversion of the ambient mechanical energy into electricity is most often done through inertial resonant piezoelectric microdevices. This thesis presents an extensive study of this technology and proposes a process to fabricate MEMS microgenerators with record performances compared to the state of the art. We first present a complete review of the physical and technological limits of this technology to asses the best path of improvement. Reported approaches (geometries, architectures, materials, circuits) are evaluated and figures of merit are proposed to compare the state of the art. These analyses show that the fundamental limit is the absorbed energy, as most proposals to date partially address the other limits. The absorbed energy depends on the level of vibrations available, but also on the mass of the device and its quality factor for a linear resonant generator. To guide design of prototypes, we conducted a study on the potential of autonomous sensors in vehicles. A survey of sensors present on a car was realized to estimate their compatibility with energy harvesting technologies. Vibration measurements done on a running vehicle at relevant locations showed that the energy available for MEMS devices is mostly located in a frequency range of 30 to 150 Hz and could generate power in the range of 1-10 μW per gram from a linear resonator. To limit the size of a MEMS generator capable of producing 10 μW, a higher mass density compared to silicon is needed, which motivates the development of a process that incorporates tungsten. Although the effect of tungsten on the device sensitivity is well known, we also demonstrate that it reduces the impact of the fluidic damping on the mechanical quality factor Qm. If fluidic damping is dominant, switching to tungsten can improve Qm by an order of magnitude, going from 103 to 104 in ambient air. As a result, the device efficiency is improved despite the lack of a vacuum package. We then propose a fabrication process flow to integrate 500 μm thick tungsten masses at the wafer level. This process combines wafer bonding with a 2-step wet metal etching approach. We present each of the fabrication nodes realized to demonstrate the feasibility of the process, which led to the fabrication of several prototypes. These devices are tested in the lab, with some designs demonstrating record breaking performances in term of normalized power density. Our best design is noteworthy for its figure of merit that is around 2.5 mW-s-1/(mm3(m/s2)2), which is the best reported in the state of the art. With a volume of 3.5 mm3, it operates at 552.7 Hz and produces 2.7 μW at 1.6 V RMS from an acceleration of 1 m/s2. These results therefore show that tungsten integration in MEMS microgenerators is very advantageous, allowing to reduce the gap with needs of current applications

Smart Materials and Devices for Energy Harvesting

This book is devoted to energy harvesting from smart materials and devices. It focusses on the latest available techniques recently published by researchers all over the world. Energy Harvesting allows otherwise wasted environmental energy to be converted into electric energy, such as vibrations, wind and solar energy. It is a common experience that the limiting factor for wearable electronics, such as smartphones or wearable bands, or for wireless sensors in harsh environments, is the finite energy stored in onboard batteries. Therefore, the answer to the battery “charge or change” issue is energy harvesting because it converts the energy in the precise location where it is needed. In order to achieve this, suitable smart materials are needed, such as piezoelectrics or magnetostrictives. Moreover, energy harvesting may also be exploited for other crucial applications, such as for the powering of implantable medical/sensing devices for humans and animals. Therefore, energy harvesting from smart materials will become increasingly important in the future. This book provides a broad perspective on this topic for researchers and readers with both physics and engineering backgrounds

A comparison of linear and non-linear strategies for energy harvesting from mechanical vibrations

Energy Harvesting strategies coupled with the improvement of electronics and the progressive reduction of power requirements have been widely recognized as fundamental to enable self-powered (or autonomous) devices. Among all the potential energy sources, kinetic energy stemming from mechanical vibrations has been particularly extensively investigated for EH purposes due to its characteristics of heterogeneity and ubiquity. To exploit such energy sources, a suitable coupling mechanism to convert vibrations into electric charge is required; it must take into account the wide frequency bandwidth of mechanical vibrations as encountered in everyday scenarios. This review offers an overview of linear vs. non-linear strategies for EH, with a specific focus on different approaches to implement efficient coupling mechanisms; the performances of the specific solutions covered in this work are discussed

SUSTAINABLE ENERGY HARVESTING TECHNOLOGIES – PAST, PRESENT AND FUTURE

Chapter 8: Energy Harvesting Technologies: Thick-Film Piezoelectric Microgenerato

Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm

Offshore Wind has become the most profitable renewable energy source due to the remarkable development it has experienced in Europe over the last decade. In this paper, a review of Structural Health Monitoring Systems (SHMS) for offshore wind turbines (OWT) has been carried out considering the topic as a Statistical Pattern Recognition problem. Therefore, each one of the stages of this paradigm has been reviewed focusing on OWT application. These stages are: Operational Evaluation; Data Acquisition, Normalization and Cleansing; Feature Extraction and Information Condensation; and Statistical Model Development. It is expected that optimizing each stage, SHMS can contribute to the development of efficient Condition-Based Maintenance Strategies. Optimizing this strategy will help reduce labor costs of OWTs׳ inspection, avoid unnecessary maintenance, identify design weaknesses before failure, improve the availability of power production while preventing wind turbines׳ overloading, therefore, maximizing the investments׳ return. In the forthcoming years, a growing interest in SHM technologies for OWT is expected, enhancing the potential of offshore wind farm deployments further offshore. Increasing efficiency in operational management will contribute towards achieving UK׳s 2020 and 2050 targets, through ultimately reducing the Levelised Cost of Energy (LCOE)

Autonomous Sensing Nodes for IoT Applications

The present doctoral thesis fits into the energy harvesting framework, presenting the development of low-power nodes compliant with the energy autonomy requirement, and sharing common technologies and architectures, but based on different energy sources and sensing mechanisms. The adopted approach is aimed at evaluating multiple aspects of the system in its entirety (i.e., the energy harvesting mechanism, the choice of the harvester, the study of the sensing process, the selection of the electronic devices for processing, acquisition and measurement, the electronic design, the microcontroller unit (MCU) programming techniques), accounting for very challenging constraints as the low amounts of harvested power (i.e., [μW, mW] range), the careful management of the available energy, the coexistence of sensing and radio transmitting features with ultra-low power requirements. Commercial sensors are mainly used to meet the cost-effectiveness and the large-scale reproducibility requirements, however also customized sensors for a specific application (soil moisture measurement), together with appropriate characterization and reading circuits, are also presented. Two different strategies have been pursued which led to the development of two types of sensor nodes, which are referred to as 'sensor tags' and 'self-sufficient sensor nodes'. The first term refers to completely passive sensor nodes without an on-board battery as storage element and which operate only in the presence of the energy source, provisioning energy from it. In this thesis, an RFID (Radio Frequency Identification) sensor tag for soil moisture monitoring powered by the impinging electromagnetic field is presented. The second term identifies sensor nodes equipped with a battery rechargeable through energy scavenging and working as a secondary reserve in case of absence of the primary energy source. In this thesis, quasi-real-time multi-purpose monitoring LoRaWAN nodes harvesting energy from thermoelectricity, diffused solar light, indoor white light, and artificial colored light are presented

Advances in Piezoelectric Transducers

The piezoelectric transducer converts electric signals into mechanical vibrations or vice versa by utilizing the morphological change of a crystal which occurs on voltage application, or conversely by monitoring the voltage generated by a pressure applied on a crystal. This book reports on the state of the art research and development findings on this very broad matter through original and innovative research studies exhibiting various investigation directions. The present book is a result of contributions of experts from international scientific community working in different aspects of piezoelectric transducers. The text is addressed not only to researchers, but also to professional engineers, students and other experts in a variety of disciplines, both academic and industrial seeking to gain a better understanding of what has been done in the field recently, and what kind of open problems are in this area

Ultra-Low Power Transmitter and Power Management for Internet-of-Things Devices

Two of the most critical components in an Internet-of-Things (IoT) sensing and transmitting node are the power management unit (PMU) and the wireless transmitter (Tx). The desire for longer intervals between battery replacements or a completely self-contained, battery-less operation via energy harvesting transducers and circuits in IoT nodes demands highly efficient integrated circuits. This dissertation addresses the challenge of designing and implementing power management and Tx circuits with ultra-low power consumption to enable such efficient operation. The first part of the dissertation focuses on the study and design of power management circuits for IoT nodes. This opening portion elaborates on two different areas of the power management field: Firstly, a low-complexity, SPICE-based model for general low dropout (LDO) regulators is demonstrated. The model aims to reduce the stress and computation times in the final stages of simulation and verification of Systems-on-Chip (SoC), including IoT nodes, that employ large numbers of LDOs. Secondly, the implementation of an efficient PMU for an energy harvesting system based on a thermoelectric generator transducer is discussed. The PMU includes a first-in-its-class LDO with programmable supply noise rejection for localized improvement in the suppression. The second part of the dissertation addresses the challenge of designing an ultra- low power wireless FSK Tx in the 900 MHz ISM band. To reduce the power consumption and boost the Tx energy efficiency, a novel delay cell exploiting current reuse is used in a ring-oscillator employed as the local oscillator generator scheme. In combination with an edge-combiner PA, the Tx showed a measured energy efficiency of 0.2 nJ/bit and a normalized energy efficiency of 3.1 nJ/(bit∙mW) when operating at output power levels up to -10 dBm and data rates of 3 Mbps. To close this dissertation, the implementation of a supply-noise tolerant BiCMOS ring-oscillator is discussed. The combination of a passive, high-pass feedforward path from the supply to critical nodes in the selected delay cell and a low cost LDO allow the oscillator to exhibit power supply noise rejection levels better than –33 dB in experimental results