Power electronic interfaces for piezoelectric energy harvesters

Motion-driven energy harvesters can replace batteries in low power wireless sensors, however selection of the optimal type of transducer for a given situation is difficult as the performance of the complete system must be taken into account in the optimisation. In this thesis, a complete piezoelectric energy harvester system model including a piezoelectric transducer, a power conditioning circuit, and a battery, is presented allowing for the first time a complete optimisation of such a system to be performed. Combined with previous work on modelling an electrostatic energy harvesting system, a comparison of the two transduction methods was performed. The results at 100 Hz indicate that for small MEMS devices at low accelerations, electrostatic harvesting systems outperform piezoelectric but the opposite is true as the size and acceleration increases. Thus the transducer type which achieves the best power density in an energy harvesting system for a given size, acceleration and operating frequency can be chosen. For resonant vibrational energy harvesting, piezoelectric transducers have received a lot of attention due to their MEMS manufacturing compatibility with research focused on the transduction method but less attention has been paid to the output power electronics. Detailed design considerations for a piezoelectric harvester interface circuit, known as single-supply pre-biasing (SSPB), are developed which experimentally demonstrate the circuit outperforming the next best known interface's theoretical limit. A new mode of operation for the SSPB circuit is developed which improves the power generation performance when the piezoelectric material properties have degraded. A solution for tracking the maximum power point as the excitation changes is also presented.Open Acces

Functional modelling and prototyping of electronic integrated kinetic energy harvesters

The aim of developing infinite-life autonomous wireless electronics, powered by the energy of the surrounding environment, drives the research efforts in the field of Energy Harvesting. Electromagnetic and piezoelectric techniques are deemed to be the most attractive technologies for vibrational devices. In the thesis, both these technologies are investigated taking into account the entire energy conversion chain. In the context of the collaboration with the STMicroelectronics, the project of a self-powered Bluetooth step counter embedded in a training shoe has been carried out. A cylindrical device 27 × 16mm including the transducer, the interface circuit, the step-counter electronics and the protective shell, has been developed. Environmental energy extraction occurs exploiting the vibration of a permanent magnet in response to the impact of the shoe on the ground. A self-powered electrical interface performs maximum power transfer through optimal resistive load emulation and load decoupling. The device provides 360 μJ to the load, the 90% of the maximum recoverable energy. The energy requirement is four time less than the provided and the effectiveness of the proposed device is demonstrated also considering the foot-steps variability and the performance spread due to prototypes manufacturing. In the context of the collaboration with the G2Elab of Grenoble and STMicroelectronics, the project of a piezoelectric energy arvester has been carried out. With the aim of exploiting environmental vibrations, an uni-morph piezoelectric cantilever beam 60×25×0.5mm with a proof mass at the free-end has been designed. Numerical results show that electrical interfaces based on SECE and sSSHI techniques allows increasing performance up to the 125% and the 115% of that in case of STD interface. Due to the better performance in terms of harvested power and in terms of electric load decoupling, a self-powered SECE interface has been prototyped. In response to 2 m/s2 56,2 Hz sinusoidal input, experimental power recovery of 0.56mW is achieved demonstrating that the device is compliant with standard low-power electronics requirements

A Multi-Source Harvesting System Applied to Sensor-Based Smart Garments for Monitoring Workers’ Bio-Physical Parameters in Harsh Environments

This paper describes the development and characterization of a smart garment for monitoring the environmental and biophysical parameters of the user wearing it; the wearable application is focused on the control to workers’ conditions in dangerous workplaces in order to prevent or reduce the consequences of accidents. The smart jacket includes flexible solar panels, thermoelectric generators and flexible piezoelectric harvesters to scavenge energy from the human body, thus ensuring the energy autonomy of the employed sensors and electronic boards. The hardware and firmware optimization allowed the correct interfacing of the heart rate and SpO2 sensor, accelerometers, temperature and electrochemical gas sensors with a modified Arduino Pro mini board. The latter stores and processes the sensor data and, in the event of abnormal parameters, sends an alarm to a cloud database, allowing company managers to check them via a web app. The characterization of the harvesting subsection has shown that ≈ 265 mW maximum power can be obtained in a real scenario, whereas the power consumption due to the acquisition, processing and BLE data transmission functions determined that a 10 mAh/day charge is required to ensure the device’s proper operation. By charging a 380 mAh Lipo battery in a few hours by means of the harvesting system, an energy autonomy of 23 days was obtained, in the absence of any further energy contribution

A Smart Knee Implant Using Triboelectric Energy Harvesters

Although the number of total knee replacement (TKR) surgeries is growing rapidly, functionality and pain-reduction outcomes remain unsatisfactory for many patients. Continual monitoring of knee loads after surgery offers the potential to improve surgical procedures and implant designs. The goal of this study is to characterize a triboelectric energy harvester under body loads and to design compatible frontend electronics to digitize the load data. The harvester prototype would be placed between the tibial component and polyethylene bearing of a TKR implant. The harvester generates power from the compressive load. To examine the harvester output and the feasibility of powering a digitization circuitry, a triboelectric energy harvester prototype is fabricated and tested. An axial tibiofemoral load profile from normal walking (gait) is approximated as a 1 Hz sine wave signal and is applied to the harvester. Because the root mean square of voltages generated via this phenomenon is proportional to the applied load, the device can be simultaneously employed for energy harvesting and load sensing. With an approximated knee cyclic load of 2.3 kN at 1 Hz, the harvester generated output voltage of 18 V RMS, and an average power of 6 µW at the optimal resistance of 58MΩ. The harvested signal is rectified through a negative voltage converter rectifier and regulated through a linear-dropout regulator with a combined efficiency of 71%. The output of the regulator is used to charge a supercapacitor. The energy stored in the supercapacitor is used for low resolution sensing of the load through a peak detector and analog-to-digital converter. According to our analysis, sensing the load several times a day is feasible by relying only on harvested power. The results found from this work demonstrate that triboelectric energy harvesting is a promising technique for self-powering load sensors inside knee implants

ENERGY HARVESTING TECHNIQUES IN WIRELESS SENSOR NETWORKS

Batteries are the main source of energy for low-power electronics such as micro-electro mechanical systems (MEMS), wireless sensor networks, embedded devices for remote sensing and control, etc. With the limited capacity of finite power sources and the need for supplying energy for the lifetime of a system/device there is a requirement for self-powered devices. Using conventional batteries is not always good design solution because batteries require human intervention to replace them (very often in hard-accessible and harsh-environmental conditions). Therefore, acquiring the electrical power, by using an alternative source of energy that is needed to operate these devices is a major concern. The process of extracting energy from the surrounding environment and converting it into consumable electrical energy is known as energy harvesting or power scavenging. The energy harvesting sources can be used to increase the lifetime and capability of the devices by either replacing or augmenting the battery usage. There are various forms of energy that can be scavenged, like solar, mechanical, thermal, and electromagnetic. Nowadays, there is a big interest in the field of research related to energy harvesting. This paper represents a survey for identifying the sources of energy harvesting and describes the basic operation of principles of the most common energy harvester. As first, we present, in short, the conversion principles of single energy source harvesting systems and point to their benefits and limitations in their usage. After that, hybrid structures of energy harvesters which simultaneously combine scavenged power from different ambient sources (solar, thermoelectric, electromagnetic), with aim to support higher load at the output, are considered

Architecture of Micro Energy Harvesting Using Hybrid Input of RF, Thermal and Vibration for Semi-Active RFID Tag

This research work presents a novel architecture of Hybrid Input Energy Harvester (HIEH) system for semi-active Radio Frequency Identification (RFID) tags. The proposed architecture consists of three input sources of energy which are radio frequency signal, thermal and vibration. The main purpose is to solve the semi-active RFID tags limited lifespan issues due to the need for batteries to power their circuitries. The focus will be on the rectifiers and DC-DC converter circuits with an ultra-low power design to ensure low power consumption in the system. The design architecture will be modelled and simulated using PSpice software, Verilog coding using Mentor Graphics and real-time verification using field-programmable gate array board before being implemented in a 0.13 µm CMOS technology. Our expectations of the results from this architecture are it can deliver 3.3 V of output voltage, 6.5 mW of output power and 90% of efficiency when all input sources are simultaneously harvested. The contribution of this work is it able to extend the lifetime of semi-active tag by supplying electrical energy continuously to the device. Thus, this will indirectly  reduce the energy limitation problem, eliminate the dependency on batteries and make it possible to achieve a batteryless device.This research work presents a novel architecture of Hybrid Input Energy Harvester (HIEH) system for semi-active Radio Frequency Identification (RFID) tags. The proposed architecture consists of three input sources of energy which are radio frequency signal, thermal and vibration. The main purpose is to solve the semi-active RFID tags limited lifespan issues due to the need for batteries to power their circuitries. The focus will be on the rectifiers and DC-DC converter circuits with an ultra-low power design to ensure low power consumption in the system. The design architecture will be modelled and simulated using PSpice software, Verilog coding using Mentor Graphics and real-time verification using field-programmable gate array board before being implemented in a 0.13 µm CMOS technology. Our expectations of the results from this architecture are it can deliver 3.3 V of output voltage, 6.5 mW of output power and 90% of efficiency when all input sources are simultaneously harvested. The contribution of this work is it able to extend the lifetime of semi-active tag by supplying electrical energy continuously to the device. Thus, this will indirectly  reduce the energy limitation problem, eliminate the dependency on batteries and make it possible to achieve a batteryless device

Energy autonomous systems : future trends in devices, technology, and systems

The rapid evolution of electronic devices since the beginning of the nanoelectronics era has brought about exceptional computational power in an ever shrinking system footprint. This has enabled among others the wealth of nomadic battery powered wireless systems (smart phones, mp3 players, GPS, …) that society currently enjoys. Emerging integration technologies enabling even smaller volumes and the associated increased functional density may bring about a new revolution in systems targeting wearable healthcare, wellness, lifestyle and industrial monitoring applications

Nonlinear vibration energy harvesters for powering the internet of things

The ever decreasing power consumption in electronic devices and sensors have facilitated the development of autonomous wireless sensor nodes (WSNs), which ushered in the era of the Internet of Things (IoT). However, the problem of long-term power supply to the numerous WSNs pervasively dispersed to enable the IoT is yet to be resolved. This work focuses on the development of novel vibration energy harvesting (VEH) devices and technologies for effective transduction of mostly wide-band and noisy ambient mechanical vibrations to power WSNs. In this thesis meso-scale and MEMS-scale nonlinear and frequency tunable VEH devices have been designed, fabricated and characterized. The first meso-scale VEH prototype developed in this thesis combines a nonlinear bistable oscillator with mechanical impact induced nonlinearity, which exhibits upto 118% broadening in the frequency response over a standalone bistable system. The second meso-scale prototype combines magnetic repulsion induced bistable nonlinearity with stretching induced monostable cubic nonlinearity in a single device structure. The device effectively merged the beneficial features of the individual nonlinear bistable and monostable systems, and demonstrates upto 85% enhanced spectral performance compared to the bistable device. The third prototype is a MEMS-scale device fabricated using spiral silicon spring structure and double-layer planar micro-coils. A magnetic repulsion induced frequency tuning mechanism was incorporated in the prototype, and it was demonstrated that both linear and nonlinear hysteretic frequency responses could be tuned (by upto 18.6%) to match various ambient vibration frequencies. In order to enhance the power generating capability of MEMS-scale electromagnetic devices, an ultra-dense multi-layer micro-coil architecture has been developed. The proposed ultra-dense micro-coil is designed to incorporate double number of turns within the same volume as a conventional micro-coil, and significantly enhance the magnetic flux linkage gradient resulting in higher power output (~4 times). However, attempts to fabricate the ultra-dense coil have not been successful due to lack of proper insulation between the successive coil layers. Finally, a power management system combining diode equivalent low voltage drop (DELVD) circuit and a boost regulator module was developed. It was demonstrated that energy harvested from harmonic and bandlimited random vibrations using linear, nonlinear bistable, and combined nonlinear VEH devices could be conditioned into usable electricity by the power management system with 60% - 75% efficiency. In addition to developing new prototypes and techniques, this thesis recommends directions towards future research for further improvement in vibration energy harvesting devices and technologies

Design and optimization of piezoelectric MEMS vibration energy harvesters

Low-power electronic applications are normally powered by batteries, which have to deal with stringent lifetime and size constraints. To enhance operational autonomy, energy harvesting from ambient vibration by micro-electromechanical systems (MEMS) has been identified as a promising solution to this universal problem. In this thesis, multiple configurations for MEMS-based piezoelectric energy harvesters are studied. To enhance their performances, automated design and optimization methodologies with minimum human efforts are proposed. Firstly, the analytic equations to estimate resonant frequency and amplitude of the harvested voltage for two different configurations of unimorph MEMS piezoelectric harvesters (i.e., with and without integration of a proof mass) are presented with their accuracy validated by using finite element method (FEM) simulation and prototype measurement. Thanks to their high accuracy, we use these analytic equations as fitness functions of genetic algorithm (GA), an evolutionary computation method for optimization problems by mimicking biological evolution. By leveraging the micro-fabrication process, we demonstrate that the GA can optimize the mechanical geometry of the prototyped harvester effectively and efficiently, whose peak harvested voltage increases from 310 mV to 1900 mV at the reduced resonant frequency from 886 Hz to 425 Hz with the highest normalized voltage density of 163.88 among the alternatives. With an intention of promoting uniform stress distribution along the piezoelectric cantilever and providing larger area for placing proof masses, in this thesis a T-shaped cantilever structure with two degrees-of-freedom (DOF) is proposed. Thanks to this special configuration, a considerable amount of stress/strain can be obtained from the tip part of the structure during the vibration, in addition to the anchor region. An analytic model for computing the frequency response of the proposed structure is derived, and the harvester performance is studied analytically, numerically and experimentally. The conventional MEMS energy harvesters can only generate voltage disadvantageously in a narrow bandwidth at higher frequencies. Therefore, in this thesis we further propose a piezoelectric MEMS harvester with the capability of vibrating in multiple DOF, whose operational bandwidth is enhanced by taking advantage of both multimodal and nonlinear mechanisms. The proposed harvester has a symmetric structure with a doubly-clamped configuration enclosing three proof masses in distinct locations. Thanks to the uniform mass distribution, the energy harvesting efficiency can be considerably enhanced. To determine the optimum geometry for the preferred nonlinear behavior, we have also used optimization methodology based on GA. The prototype measurements demonstrate that our proposed piezoelectric MEMS harvester is able to generate voltage at 227 Hz (the first mode), 261.8 Hz (the second mode), and 286 Hz (the third mode). When the device operates at its second mode frequency, nonlinear behavior can be obtained with extremely small magnitude of base excitation (i.e., 0.2 m/s²). Its normalized power density (NPD) of 595.12 (μW·cm⁻³·m⁻²·s⁴) is found to be superior to any previously reported piezoelectric MEMS harvesters in the literature. In this dissertation, we also propose a piezoelectric MEMS vibration energy harvester with the capability of oscillating at ultralow (i.e., less than 200 Hz) resonant frequency. The mechanical structure of the proposed harvester is comprised of a doubly clamped cantilever with a serpentine pattern associated with several discrete masses. In order to obtain the optimal physical aspects of the harvester and speed up the design process, we have utilized a deep neural network, as an artificial intelligence (AI) method. Firstly, the deep neural network was trained, and then this trained network was integrated with the GA to optimize the harvester geometry to enhance its performance in terms of both resonant frequency and generated voltage. Our numerical results confirm that the accuracy of the network in prediction is above 90%. As a result, by taking advantage of this efficient AI-based performance estimator, the GA is able to reduce the device resonant frequency from 169Hz to 110.5Hz and increase its efficiency on harvested voltage from 2.5V to 3.4V under 0.25g excitation. To improve both durability and energy conversion efficiency of the piezoelectric MEMS harvesters, we further propose a curve-shaped anchoring scheme in this thesis. A doubly clamped curve beam with a mass at its center is considered as an anchor, while a straight beam with proof mass is integrated to the center of this anchor. To assess the fatigue damage, which is actually critical to the micro-sized silicon-based piezoelectric harvesters, we have utilized the Coffin-Manson method and FEM to study the fatigue lifetime of the proposed geometry comprehensively. Our proposed piezoelectric harvester has been fabricated and its capability in harnessing the vibration energy has been examined numerically and experimentally. It is found that the harvested energy can be enlarged by a factor of 2.66, while this improvement is gained by the resonant frequency reduction and failure force magnitude enlargement, in comparison with the conventional geometry of the piezoelectric MEMS harvesters