fluttering energy harvester for autonomous powering flehap aeroelastic characterisation and preliminary performance evaluation

Abstract Significant efforts are being devoted in order to develop efficient and reliable energy harvesters based on interactions between structures and environmental fluid flows such as wind or marine currents. In this framework, a fully-passive energy harvester of centimetric size employing an elastically bounded wing has been developed. The system exploits the coupled-mode flutter, leading in certain conditions to finite amplitude and self-sustained oscillations. Electrical output power levels up to 15[mW] have been reached by an experimental prototype within a wind range between 2 and 5 [m/s] by means of electromagnetic coupling as the conversion strategy. Focusing on the aeroelastic point of view, it is crucial to investigate how the kinematics (i.e. flapping amplitude and frequency, phase between the pitch and plunge motion DoFs) varies with the main parameters (e.g. wind velocity and wing geometry), in order to identify the optimal conditions for potential harvesting. With this goal in mind, we present and discuss the results for a representative configuration of the device (first without the extraction mechanism), exploring the behavior within the design wind range, combining wind-tunnel experiments, three-dimensional CFD simulations and the development of a quasi-steady phenomenological model. We find that both the amplitude and the frequency of the flapping motion are maximised for a certain wind velocity. Moreover, the phase between pitch and plunge changes abruptly when close to this condition. Hence, we estimate the mechanical power that the wing is able to collect and the Betz efficiency, e.g. the ratio between the latter and the power available in the flow. The mathematical model is then enriched by additional terms mimicking an electrical resistive circuit and predictions are made regarding the extracted power and global efficiency of the system, showing the presence of optimal conditions for which these quantities are maximised. Finally, we outline future challenges in the harvester development towards a realistic deployment

An impact-based broadband aeroelastic energy harvester for concurrent wind and base vibration energy harvesting

© 2017 This paper proposes a novel broadband energy harvester to concurrently harvest energy from base vibrations and wind flows by utilizing a mechanical stopper. A problem for a conventional wind energy harvester is that it can only effectively harness energy from two types of excitations around its resonance frequency. The proposed design consists of a D-shape-sectioned bluff body attached to a piezoelectric cantilever, and a mechanical stopper fixed at the bottom of the cantilever which introduces piecewise linearity through its impact with the bluff body. The quasi-periodic oscillations are converted to periodic vibration due to the introduction of the mechanical stopper, which forces the two excitation frequencies to lock into each other. Broadened bandwidth for effective concurrent energy harvesting is thus achieved, and at the same time, the beam deflection is slightly mitigated and fully utilized for power conversion. The experiment shows that with the stopper-bluff body distance of 19.5 mm, the output power from the proposed harvesting device increases steadily from 3.0 mW at 17.3 Hz to 3.8 mW at 19.1 Hz at a wind speed of 5.5 m/s and a base acceleration of 0.5 g. A guideline for the stopper configuration is also provided for performance enhancement of the broadband concurrent wind and vibration energy harvester

Toward Small-Scale Wind Energy Harvesting: Design, Enhancement, Performance Comparison, and Applicability

© 2017 Liya Zhao and Yaowen Yang. The concept of harvesting ambient energy as an alternative power supply for electronic systems like remote sensors to avoid replacement of depleted batteries has been enthusiastically investigated over the past few years. Wind energy is a potential power source which is ubiquitous in both indoor and outdoor environments. The increasing research interests have resulted in numerous techniques on small-scale wind energy harvesting, and a rigorous and quantitative comparison is necessary to provide the academic community a guideline. This paper reviews the recent advances on various wind power harvesting techniques ranging between cm-scaled wind turbines and windmills, harvesters based on aeroelasticities, and those based on turbulence and other types of working principles, mainly from a quantitative perspective. The merits, weaknesses, and applicability of different prototypes are discussed in detail. Also, efficiency enhancing methods are summarized from two aspects, that is, structural modification aspect and interface circuit improvement aspect. Studies on integrating wind energy harvesters with wireless sensors for potential practical uses are also reviewed. The purpose of this paper is to provide useful guidance to researchers from various disciplines interested in small-scale wind energy harvesting and help them build a quantitative understanding of this technique

Energy harvesting towards self-powered iot devices

The internet of things (IoT) manages a large infrastructure of web-enabled smart devices, small devices that use embedded systems, such as processors, sensors, and communication hardware to collect, send, and elaborate on data acquired from their environment. Thus, from a practical point of view, such devices are composed of power-efficient storage, scalable, and lightweight nodes needing power and batteries to operate. From the above reason, it appears clear that energy harvesting plays an important role in increasing the efficiency and lifetime of IoT devices. Moreover, from acquiring energy by the surrounding operational environment, energy harvesting is important to make the IoT device network more sustainable from the environmental point of view. Different state-of-the-art energy harvesters based on mechanical, aeroelastic, wind, solar, radiofrequency, and pyroelectric mechanisms are discussed in this review article. To reduce the power consumption of the batteries, a vital role is played by power management integrated circuits (PMICs), which help to enhance the system's life span. Moreover, PMICs from different manufacturers that provide power management to IoT devices have been discussed in this paper. Furthermore, the energy harvesting networks can expose themselves to prominent security issues putting the secrecy of the system to risk. These possible attacks are also discussed in this review article

Numerical Study in Wind Energy Extraction from Controlled Limit-Cycle Oscillations in Modified Glauert Airfoil

Typically, wind energy harvesting technology employs wind turbines. Towards the goal of meeting increasing energy needs with renewable energy sources a novel wind energy harvesting scheme is considered, utilizing a modified Glauert (MG) airfoil experiencing aeroelastic limit cycle oscillation (LCO) from which energy may be extracted. Synthetic jet actuators (SJA)s are used along with the unique geometry of the MG airfoil to control flow separation and amplify the LCO and energy generation potential of the system. The discussed wind energy harvesting scheme could provide flexibility in allowing installations previously unsuitable to wind turbines due to geometric or low wind velocity constraints. Without SJA control at 7 m/s wind speed, predicted net power output is 2.35 W per meter span. With SJA control, this increases to 4.05 W. Towards the study of an MG airfoil under LCO, this thesis evaluates variable-fidelity numerical schemes. A high-fidelity implicit large eddy simulation (ILES) solver FDL3DI is employed to directly compute the flow field around the moving airfoil, and especially the effects of SJA control. For a low-fidelity tool, the panel method solver with boundary layer prediction XFOIL is used. Both numerical tools compare well to steady-state experimental results. The MG airfoil geometry exhibits LCO below the velocities predicted by inviscid unsteady thin airfoil theory (UTAT) due to separation near the rear of the airfoil, including with only 1 degree of freedom (DOF). Both simple open- and closed-loop controllers show success in amplifying plunging LCO motion by activating SJAs with the natural frequency of plunging. When the low fidelity tool is complete, it can be used for fast structural, control, and geometric optimization to further increase the energy harvesting potential of the system

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