Advances in mechatronics have renewed interest in the harvesting and storage of ambient vibration energy. This work documents recent efforts to model a novel electromagnetic transducer design that is intended for use in energy harvesting. The thesis details methods of experimental characterization as well as model validation. Also presented are methods of state space and parametric modelling eforts. In addition, this thesis presents equivalent electrical circuit models with a focus on switched pulse-width-modulated topologies that seek to maximize harvested energy. / Master of Science

In a wide range of industries, machine condition monitoring is one of the most cost effective ways to minimise maintenance efforts and machine downtime. To implement such a system, wireless solutions have increasingly become an attractive proposition due to the ease of installation and minimal infrastructure alternation. However, currently most wireless sensors in the world are powered by a finite battery source. The dependence of batteries not only requires frequent maintenance, but also has adverse environmental consequences associated with battery disposal. These reasons render massive deployment of wireless sensors in the industry problematic. With the advances in semiconductors, power consumption of wireless sensors has been continuously decreasing. It is an inevitable trend for self-powered wireless sensors to emerge and become the norm for machine and environmental monitoring. In this research, vibration is chosen to be the energy source to enable self-powered wireless sensors due to its ubiquitousness in machinery and industrial environments. As a result of relying on resonance, the biggest challenge for vibration-based energy harvesters is their narrow bandwidth. Even a small deviation of the vibration frequency can dramatically reduce the power output. The primary goal of this research is to address this problem. In particular, Piezoelectric generators are identified to be the most suitable technology. In this work, extensive theoretical and experimental studies are conducted in single mass and multi-modal harvesters, and in resonance tuning harvesters by modulus and impedance matching as well as by mechanical actuation. Mathematical modelling plays a significant role in energy harvester designs. A dynamic model that generalises the single degree of freedom models and the continuum models is derived and validated by experiments. The model serves as the building block for the whole research, and it is further refined for the investigation of modulus and impedance matching. In the study of multi-modal harvesters, a continuum model for double-mass piezoelectric cantilever beams is derived and experimentally validated. To study the feasibility of resonance tuning by mechanical means, prototypes were built and performance evaluated. This document details the theoretical basis, concepts and experimental results that extend the current knowledge in the field of energy harvesting. This research work, being highly industrially focused, is believed to be a very significant step forward to a commercial energy harvester that works for a wide range of vibration frequencies.

Simulations are a good method for the verification of the correct operation of solar-powered sensor nodes over the desired lifetime. They do, however, require accurate models to capture the influences of the loads and solar energy harvesting system. Artificial neural networks promise a simplification and acceleration of the modeling process in comparison to state-of-the-art modeling methods. This work focuses on the influence of the modeling process's different configurations on the accuracy of the model. It was found that certain parameters, such as the network's number of neurons and layers, heavily influence the outcome, and that these factors need to be determined individually for each modeled harvesting system. But having found a good configuration for the neural network, the model can predict the supercapacitor's charge depending on the solar current fairly accurately. This is also true in comparison to the reference models in this work. Nonetheless, the results also show a crucial need for improvements regarding the acquisition and composition of the neural network's training set.

The work described in this thesis is aimed at developing a novel piezoelectric cantilever energy harvesting circuit, so that more energy can be obtained from a particular piezoelectric harvester than is possible using conventional circuits. The main focus of the work was to design, build and test a proof of principle system, and not a commercial version, so as to determine any limitations to the circuit. The circuit functions by cancelling the capacitive output reactance of the piezoelectric harvester with a simulated inductance, and is based on an idea proposed by Qi in 2011. Although Qi's approach demonstrated that the circuit could function, the system proved too lossy, and so a less lossy version is attempted here. Experimental and software simulations are provided to verify the theoretical predictions. A prototype amplified inductor circuit was simulated and tested. From the simulation results, although harmonic current losses were found in the circuit, it was found that the circuit should produce an amplified effective inductance and a maximum output power of 165mW. The effective inductance is derived from the voltage across the 2H inductor, and this voltage is amplified and applied to the circuit via an inverter, to provide an extra simulated inductance, so that the overall inductance can be resonated with the piezoelectric harvester output capacitance. Hence the capacitive impedance of the harvester is nearly cancelled. The study and analysis of the amplified inductor circuit was carried out for a single cantilever harvester. Both open loop and closed loop testing of the system were carried out. The open loop test showed that the concept should function as predicted. The purpose of the closed loop test was to make the system automatically adjust for different resonance frequencies. The circuit was tested at 52Vpp inverter output voltage, and demonstrated a harvested power of 145.5mW. Experimental results show that the harvester output power is boosted from 8.8mW as per the manufacturer data sheet to 145.5mW (16.5 times). This is approximately double the power available using circuits described in the literature.

Electromechanical modeling efforts in the research field of vibration-based energy harvesting have been mostly focused on deterministic forms of vibrational input as in the typical case of harmonic excitation at resonance. However, ambient vibrational energy often has broader frequency content than a single harmonic, and in many cases it is entirely stochastic. As compared to the literature of harvesting deterministic forms of vibrational energy, few authors presented modeling approaches for energy harvesting from broadband random vibrations. These efforts have combined the input statistical information with the single-degree-of-freedom (SDOF) dynamics of the energy harvester to express the electromechanical response characteristics. In most cases, the vibrational input is assumed to have broadband frequency content, such as white noise. White noise has a flat power spectral density (PSD) that might in fact excite higher vibration modes of an electroelastic energy harvester. In particular, cantilevered piezoelectric energy harvesters constitute such continuous electroelastic systems with more than one vibration mode. The main component of this thesis presents analytical and numerical electroelastic modeling, simulations, and experimental validations of piezoelectric energy harvesting from broadband random excitation. The modeling approach employed herein is based on distributed-parameter electroelastic formulation to ensure that the effects of higher vibration modes are included. The goal is to predict the expected value of the power output and the mean-square shunted vibration response in terms of the given PSD or time history of the random vibrational input. The analytical method is based on the PSD of random base excitation and distributed-parameter frequency response functions of the coupled voltage output and shunted vibration response. The first one of the two numerical solution methods employs the Fourier series representation of the base acceleration history in a Runge-Kutta-based ordinary differential equation solver while the second method uses an Euler-Maruyama scheme to directly solve the resulting electroelastic stochastic differential equations. The analytical and numerical simulations are compared with several experiments for a brass-reinforced PZT-5H cantilever bimorph under different random excitation levels.In addition to base-excited cantilevered configurations, energy harvesting using prismatic piezoelectric stack configurations is investigated. Electromechanical modeling and numerical simulations are given and validated through experiments for a multi-layer PZT-5H stack. After validating the electromechanical models for specific experimentally configurations and samples, various piezoelectric materials are compared theoretically for energy harvesting from random vibrations. Finally, energy harvesting from narrowband random vibrationsusing both configurations are investigated theoretically and experimentally.

The development of self-powered wireless sensor networks for structural and machinery health monitoring has attracted considerable attention in the research field during the last decade. Since the low-duty-cycle wireless sensor networks have significantly reduced the power requirements to the range of tens to hundreds of microwatts, it is possible to harvest environmental energy as the power supply instead of using batteries. Vibration energy harvesting using piezoelectric materials has become the most popular technique, which has a good potential to generate adequate power. However, there is a limitation for the conventional beam-shaped harvester designs in real applications due to their limited bandwidth. In order to overcome this limitation, the essential objective of this thesis is to develop harvesters with multi-resonance structures. The multi-resonance harvester with good broadband performance can achieve close resonance frequencies and relatively large power output in each vibration mode. The main tasks and contributions of this thesis are summarised as follows: • A parametric analysis is presented to determine how the modal structural and electromechanical performances of cantilevered beam harvesters are affected by two modal factors designated as mass ratio and electromechanical coupling coefficient (EMCC). The modal performance of using rectangular, convergent and divergent tapered configurations with and without extra masses are systematically analysed by geometric variation using the finite element analysis (FEA) software ABAQUS. • A modal approach using the two modal factors to evaluate the modal performance of harvesters is introduced and a configurational optimization strategy based on the modal approach is developed to pre-select the configurations of multi-resonance harvesters with better modal structural performance and close resonance frequencies in multiple modes. Using this optimization strategy obviates the need to run the full analysis at the first stage. • A novel two-layer stacked harvester, which consists of a base cantilevered beam that is connected to an upper beam by a rigid mass, is developed. By altering the dimensions and the locations of the masses, the two-layer harvester can generate two close resonance frequencies with relatively large power output. The effects of using rectangular, convergent and divergent tapered beam configurations are systematically analysed. • Multi-layer stacked harvesters with up to five layers are developed. The three-layer harvesters with different mass positions, which can generate three close resonance frequencies, are optimized using the configurational optimization strategy. • A novel doubly-clamped multi-layer harvester, which is able to generate five close resonance frequencies with relatively large power output, is developed and thoroughly analysed. • An experimental study of the multi-layer stacked harvester is presented to validate the simulated results and the configurational optimization strategy. • An experimental study of the two-layer stacked harvester using high performance single crystal piezoelectric material PIMNT is presented. The harvester using PIMNT can generate nearly 10 times larger power output and 3.5 times wider bandwidth than using PZT. Besides, by modifying the location of the piezoelectric layer, anti-resonances between two adjacent modes can be eliminated.

Vibration-based energy harvesting using piezoelectric materials have been investigated by several research groups with the aim of harvesting maximum energy and providing power to low-powered wireless electronic systems for their entire operational life. The electromechanical coupling effect introduced by the piezoelectric vibration energy harvesting (PVEH) mechanism presents modelling challenges. For this reason, there has been a continuous effort to develop different modelling techniques to describe the PVEH mechanism and its effects on the dynamics of the system. The overall aims of this thesis are twofold: (1) a thorough theoretical and experimental analysis of a PVEH beam or assembly of beams; (2) an in-depth analytical and experimental investigation of the novel concept of a dual function piezoelectric vibration energy harvester beam/tuned vibration absorber (PVEH/TVA) or 'electromechanical TVA' and its potential application to vibration control. The salient novel contributions of this thesis can be summarised as follows: (i) An in-depth experimental validation of a PVEH beam model based on the analytical modal analysis method (AMAM), with the investigations conducted over a wider frequency range than previously tested. (ii) The precise identification of the electrical loads that harvest maximum power and that induce maximum electrical damping. (iii) A thorough investigation of the influence of mechanical damping on PVEH beams. (iv) A procedure for the exact modelling of PVEH beams, and assemblies of such beams, using the dynamic stiffness matrix (DSM) method. (v) A procedure to enhance the power output from a PVEH beam through the application of a tip rotational restraint and the use of segmented electrodes. (vi) The theoretical basis for the novel concept of a dual function PVEH beam/TVA, and its realisation and experimental validation for a prototype device. A thorough experimental validation of a cantilever piezoelectric bimorph energy harvester without a tip mass is presented under random excitation. The study provided a deep insight into the effect of PVEH on the dynamics of the system for variations in electrical load. An alternative modelling technique to AMAM, based on the DSM, is introduced for PVEH beams. Unlike AMAM, the DSM is exact, since it is based on the exact solution to the bending wave equation. It also readily lends itself to the modelling of beams with different boundary conditions or assemblies of beams of different crosssections. AMAM is shown to converge to DSM if a sufficiency of modes is used. Finally, an in-depth theoretical and experimental investigation of a prototype PVEHbeam/TVA device is presented. This device comprises a pair of bimorphs shunted by R-L-C circuitry and can be used as a tuned mass damper (TMD) to attenuate a vibration mode of a generic structure. The optimal damping required by this TMD is generated by the PVEH effect of the bimorphs. Such a device combines the advantages of conventional mechanical and electrical TVAs, overcoming their relative disadvantages. The results demonstrate that the ideal degree of attenuation can be achieved by the proposed device through appropriate tuning of the circuitry, thereby presenting the prospect of a novel class of 'electromechanical' tuned vibration absorbers.

Wireless sensor networks(WSNs) have a diverse set of applications such as military surveillance, health and environmental monitoring, and home automation. Sensor nodes are equipped with pre-charged batteries, which drain out when the nodes sense, process, and communicate data. Eventually, the nodes of the WSN die and the network dies. Energy harvesting(EH) is a green alternative to solve the limited lifetime problem in WSNs. EH nodes recharge their batteries by harvesting ambient energy such as solar, wind, and radio energy. However, due to the randomness in the EH process and the limited amounts of energy that can be harvested, the EH nodes are often intermittently available. Therefore, even though EH nodes live perpetually, they do not cater to the network continuously. We focus on the energy-efficient design of WSNs that incorporate EH, and investigate the new design trade-offs that arise in exploiting the potentially scarce and random energy arrivals and channel fading encountered by the network. To this end, firstly, we compare the performance of conventional, all-EH, and hybrid WSNs, which consist of both conventional and EH nodes. We then study max function computation, which aims at energy-efficient data aggregation, in EH WSNs. We first argue that the conventional performance criteria used for evaluating WSNs, which are motivated by lifetime, and for evaluating EH networks are at odds with each other and are unsuitable for evaluating hybrid WSNs. We propose two new and insightful performance criteria called the k-outage and n-transmission durations to evaluate and compare different WSNs. These criteria capture the effect of the battery energies of the nodes and the channel fading conditions on the network operations. We prove two computationally-efficient bounds for evaluating these criteria, and show their use in a cost-constrained deployment of a WSN involving EH nodes. Next, we study the estimation of maximum of sensor readings in an all-EH WSN. We analyze the mean absolute error(MAE) in estimating the maximum reading when a random subset of the EH nodes periodically transmit their readings to the fusion node. We determine the optimal transmit power and the number of scheduled nodes that minimize the MAE. We weigh the benefits of the availability of channel information at the nodes against the cost of acquiring it. The results are first developed assuming that the readings are transmitted with infinite resolution. The new trade-offs that arise when quantized readings are instead transmitted are then characterized.Our results hold for any distribution of sensor readings, and for any stationary and ergodic EH process.

Real time information is essential in many businesses and as a method to inform employees and consumers, so that they can make informed decisions. In offices, warehouse and stores it can be advantageous to have tens to hundreds of smaller displays to deliver a variety of information. This paper details the design, implementation and testing of a wireless low power solar powered display system as a solution to deliver real time information. The system uses an Organic LCD to maintain an image for years on no power and uses very little power to update and refresh the display. The system uses off- the-shelf components to achieve multiple updates per day and, with the right lighting conditions, can perform up to one refresh per minute. The system is entirely powered by incandescent light, has a built in radio, and utilizes capacitors to store charge and deliver power, removing the need for rechargeable batteries. The wireless signal works at 2.4GHz and uses the low power 802.15.4 protocol to send and receive data at a range of 75 feet. It has no observable issue operating in environments with 2.4GHz wireless signals, such as 802.11g. The whole system can be built for under $75.00, and takes up an area of 6" x 8" including the photovoltaic cells. / text

The objective of this research is to develop a wearable device that could harvest waste mechanical energy of the human hand movement and utilize this energy to suppress wrist tremors. Piezoelectric material is used to measure the hand movement signals, and the signal of wrist tremor is filtered to be utilized to suppress the tremor. In order to conduct the experiment of energy harvesting and tremor suppression, an experimental rig was fabricated. Two types of piezoelectric materials, PVDF (polyvinylidene fluoride) films and MFC (macro fiber composite) films, are used to harvest mechanical energy and used as actuators to suppress hand tremors. However, due to some shortages of the materials, these two types of materials are not used as actuators to suppress the wrist tremors. Thus, we use Matlab Simulink to simulate the tremor suppression with AVC (active vibration control) algorithm.