1,288 research outputs found

    Development of piezoelectric harvesters with integrated trimming devices

    Get PDF
    Piezoelectric cantilever harvesters have a large power output at their natural frequency, but in some applications the frequency of ambient vibrations is different fromthe harvester\u2019s frequency and/or ambient vibrations are periodicwith some harmonic components. To copewith these operating conditions harvesters with integrated trimming devices (ITDs) are proposed. Some prototypes are developed with the aid of an analytical model and tested with an impulsive method. Results show that a small trimming device can lower the main resonance frequency of a piezoelectric harvester of the same extent as a larger tip mass and, moreover, it generates at high frequency a second resonance peak. A multi-physics numerical finite element (FE) model is developed for predicting the generated power and for performing a stress-strain analysis of harvesters with ITDs. The numerical model is validated on the basis of the experimental results. Several configurations of ITDs are conceived and studied. Numerical results show that the harvesters with ITDs are able to generate relevant power at two frequencies, owing to the particular shape of the modes of vibration. The stress in the harvesters with ITDs is smaller than the stress in the harvester with a tip mass trimmed to the same frequency

    Vibrational energy harvesting for sensors in vehicles

    Get PDF
    The miniaturization of semiconductor technology and reduction in power requirements have begun to enable wireless self-sufficient devices, powered by ambient energy. To date the primary application lies in generating and transmitting sensory data. The number of sensors and their applications in automotive vehicles has grown drastically in the last decade, a trend that seems to continue still. Wireless self-powered sensors can facilitate current sensor systems by removing the need for cabling and may enable additional applications. These systems have the potential to provide new avenues of optimization in safety and performance.This thesis delves into the topic of vibrations as ambient energy source, primarily for sensors in automotive vehicles. The transduction of small amounts of vibrational, or kinetic, energy to electrical power, also known as vibrational energy harvesting, is an extensive field of research with a plethora of inventions. A short review is given for energy harvesters, in an automotive context, utilizing transduction through either the piezoelectric effect or magnetic induction. Two practical examples, for ambient vibration harvesting in vehicles, are described in more detail. The first is a piezoelectric beam for powering a strain sensor on the engines rotating flexplate. It makes combined use of centrifugal force, gravitational pull and random vibrations to enhance performance and reduce required system size. The simulated power output is 370 \ub5W at a rotation frequency of 10.5 Hz, with a bandwidth of 2.44 Hz. The second example is an energy harvesting unit placed on a belt buckle. It implements magnetic induction by the novel concept of a spring balance air gap of a magnetic circuit, to efficiently harvest minute vibrations. Simulations show the potential to achieve 52 \ub5W under normal road conditions driving at 70 km/h. Theoretical modeling of these systems is also addressed. Fundamental descriptions of the lumped and distributed models are given. Based on the lumped models of the piezoelectric energy harvester (PEH) and the electromagnetic energy harvester (EMEH), a unified model is described and analyzed. New insights are gained regarding the pros and cons of the two types of energy harvester run at either resonance or anti-resonance. A numerical solution is given for the exact boundary of dimensionless quality factor and dimensionless intrinsic resistance, at which the system begins to exhibit anti-resonance. Regarding the maximum achievable power, the typical PEH is favored when running the system in anti-resonance and the typical EMEH is favored at resonance. The described modeling considers all parameters of the lumped model and thus provides a useful tool for developing vibrational energy harvester prototypes

    Energy harvesting technologies for structural health monitoring of airplane components - a review

    Get PDF
    With the aim of increasing the efficiency of maintenance and fuel usage in airplanes, structural health monitoring (SHM) of critical composite structures is increasingly expected and required. The optimized usage of this concept is subject of intensive work in the framework of the EU COST Action CA18203 "Optimising Design for Inspection" (ODIN). In this context, a thorough review of a broad range of energy harvesting (EH) technologies to be potentially used as power sources for the acoustic emission and guided wave propagation sensors of the considered SHM systems, as well as for the respective data elaboration and wireless communication modules, is provided in this work. EH devices based on the usage of kinetic energy, thermal gradients, solar radiation, airflow, and other viable energy sources, proposed so far in the literature, are thus described with a critical review of the respective specific power levels, of their potential placement on airplanes, as well as the consequently necessary power management architectures. The guidelines provided for the selection of the most appropriate EH and power management technologies create the preconditions to develop a new class of autonomous sensor nodes for the in-process, non-destructive SHM of airplane components.The work of S. Zelenika, P. Gljušcic, E. Kamenar and Ž. Vrcan is partly enabled by using the equipment funded via the EU European Regional Development Fund (ERDF) project no. RC.2.2.06-0001: “Research Infrastructure for Campus-based Laboratories at the University of Rijeka (RISK)” and partly supported by the University of Rijeka, Croatia, project uniri-tehnic-18-32 „Advanced mechatronics devices for smart technological solutions“. Z. Hadas, P. Tofel and O. Ševecek acknowledge the support provided via the Czech Science Foundation project GA19-17457S „Manufacturing and analysis of flexible piezoelectric layers for smart engineering”. J. Hlinka, F. Ksica and O. Rubes gratefully acknowledge the financial support provided by the ESIF, EU Operational Programme Research, Development and Education within the research project Center of Advanced Aerospace Technology (Reg. No.: CZ.02.1.01/0.0/0.0/16_019/0000826) at the Faculty of Mechanical Engineering, Brno University of Technology. V. Pakrashi would like to acknowledge UCD Energy Institute, Marine and Renewable Energy Ireland (MaREI) centre Ireland, Strengthening Infrastructure Risk Assessment in the Atlantic Area (SIRMA) Grant No. EAPA\826/2018, EU INTERREG Atlantic Area and Aquaculture Operations with Reliable Flexible Shielding Technologies for Prevention of Infestation in Offshore and Coastal Areas (FLEXAQUA), MarTera Era-Net cofund PBA/BIO/18/02 projects. The work of J.P.B. Silva is partially supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UIDB/FIS/04650/2020. M. Mrlik gratefully acknowledges the support of the Ministry of Education, Youth and Sports of the Czech Republic-DKRVO (RP/CPS/2020/003

    MULTI‐PHYSICAL MODELLING AND PROTOTYPING OF AN ENERGY HARVESTING SYSTEM INTEGRATED IN A RAILWAY PNEUMATIC SUSPENSION

    Get PDF
    The aim of this PhD thesis is the investigation of an energy harvesting system to be integrated in a railway pneumatic spring to recovery otherwise wasted energy source from suspension vibration. Exploiting the piezoelectric effect to convert the mechanical energy into an electrical one, the final scope consists on the use of this system to power supply one or more sensors that can give useful information for the monitoring and the diagnostics of vehicle or its subsystems. Starting from the analysis of the energy sources, a multi‐physical approach to the study of an energy harvesting system is proposed to take into account all physics involved in the phenomenon, to make the most of the otherwise wasted energy and to develop a suitable and affordable tool for the design. The project of the energy harvesting device embedded in a railway pneumatic spring has been carried out by means of using a finite element technique and multi‐physics modelling activity. The possibility to combine two energy extraction processes was investigated with the purpose of making the most of the characteristics of the system and maximize the energy recovering. Exploiting commercial piezoelectric transducers, an experimental activity was conducted in two steps. A first mock‐up was built and tested on a shaker to develop the device and to tune the numerical model against experimental evidence. In the second step a fullscale prototype of an air spring for metro application with the EH system was realized. In order to test the full‐scale component, the design of a new test bench was carried out. Finally, the Air spring integrated with the EH device was tested and models validated

    Advanced Energy Harvesting Technologies

    Get PDF
    Energy harvesting is the conversion of unused or wasted energy in the ambient environment into useful electrical energy. It can be used to power small electronic systems such as wireless sensors and is beginning to enable the widespread and maintenance-free deployment of Internet of Things (IoT) technology. This Special Issue is a collection of the latest developments in both fundamental research and system-level integration. This Special Issue features two review papers, covering two of the hottest research topics in the area of energy harvesting: 3D-printed energy harvesting and triboelectric nanogenerators (TENGs). These papers provide a comprehensive survey of their respective research area, highlight the advantages of the technologies and point out challenges in future development. They are must-read papers for those who are active in these areas. This Special Issue also includes ten research papers covering a wide range of energy-harvesting techniques, including electromagnetic and piezoelectric wideband vibration, wind, current-carrying conductors, thermoelectric and solar energy harvesting, etc. Not only are the foundations of these novel energy-harvesting techniques investigated, but the numerical models, power-conditioning circuitry and real-world applications of these novel energy harvesting techniques are also presented

    SUSTAINABLE ENERGY HARVESTING TECHNOLOGIES – PAST, PRESENT AND FUTURE

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

    High-Performance Accelerometer Based On Asymmetric Gapped Cantilevers For Physiological Acoustic Sensing

    Get PDF
    Continuous or mobile monitoring of physiological sounds is expected to play important role in the emerging mobile healthcare field. Because of the miniature size, low cost, and easy installation, accelerometer is an excellent choice for continuous physiological acoustic signal monitoring. However, in order to capture the detailed information in the physiological signals for clinical diagnostic purpose, there are more demanding requirements on the sensitivity/noise performance of accelerometers. In this thesis, a unique piezoelectric accelerometer based on the asymmetric gapped cantilever which exhibits significantly improved sensitivity is extensively studied. A meso-scale prototype is developed for capturing the high quality cardio and respiratory sounds on healthy people as well as on heart failure patients. A cascaded gapped cantilever based accelerometer is also explored for low frequency vibration sensing applications such as ballistocardiogram monitoring. Finally, to address the power issues of wireless sensors such as wireless wearable health monitors, a wide band vibration energy harvester based on a folded gapped cantilever is developed and demonstrated on a ceiling air condition unit

    Vibration Energy Harvesting for Wireless Sensors

    Get PDF
    Kinetic energy harvesters are a viable means of supplying low-power autonomous electronic systems for the remote sensing of operations. In this Special Issue, through twelve diverse contributions, some of the contemporary challenges, solutions and insights around the outlined issues are captured describing a variety of energy harvesting sources, as well as the need to create numerical and experimental evidence based around them. The breadth and interdisciplinarity of the sector are clearly observed, providing the basis for the development of new sensors, methods of measurement, and importantly, for their potential applications in a wide range of technical sectors

    MECHANICAL ENERGY HARVESTER FOR POWERING RFID SYSTEMS COMPONENTS: MODELING, ANALYSIS, OPTIMIZATION AND DESIGN

    Get PDF
    Finding alternative power sources has been an important topic of study worldwide. It is vital to find substitutes for finite fossil fuels. Such substitutes may be termed renewable energy sources and infinite supplies. Such limitless sources are derived from ambient energy like wind energy, solar energy, sea waves energy; on the other hand, smart cities megaprojects have been receiving enormous amounts of funding to transition our lives into smart lives. Smart cities heavily rely on smart devices and electronics, which utilize small amounts of energy to run. Using batteries as the power source for such smart devices imposes environmental and labor cost issues. Moreover, in many cases, smart devices are in hard-to-access places, making accessibility for disposal and replacement difficult. Finally, battery waste harms the environment. To overcome these issues, vibration-based energy harvesters have been proposed and implemented. Vibration-based energy harvesters convert the dynamic or kinetic energy which is generated due to the motion of an object into electric energy. Energy transduction mechanisms can be delivered based on piezoelectric, electromagnetic, or electrostatic methods; the piezoelectric method is generally preferred to the other methods, particularly if the frequency fluctuations are considerable. In response, piezoelectric vibration-based energy harvesters (PVEHs), have been modeled and analyzed widely. However, there are two challenges with PVEH: the maximum amount of extractable voltage and the effective (operational) frequency bandwidth are often insufficient. In this dissertation, a new type of integrated multiple system comprised of a cantilever and spring-oscillator is proposed to improve and develop the performance of the energy harvester in terms of extractable voltage and effective frequency bandwidth. The new energy harvester model is proposed to supply sufficient energy to power low-power electronic devices like RFID components. Due to the temperature fluctuations, the thermal effect over the performance of the harvester is initially studied. To alter the resonance frequency of the harvester structure, a rotating element system is considered and analyzed. In the analytical-numerical analysis, Hamilton’s principle along with Galerkin’s decomposition approach are adopted to derive the governing equations of the harvester motion and corresponding electric circuit. It is observed that integration of the spring-oscillator subsystem alters the boundary condition of the cantilever and subsequently reforms the resulting characteristic equation into a more complicated nonlinear transcendental equation. To find the resonance frequencies, this equation is solved numerically in MATLAB. It is observed that the inertial effects of the oscillator rendered to the cantilever via the restoring force effects of the spring significantly alter vibrational features of the harvester. Finally, the voltage frequency response function is analytically and numerically derived in a closed-from expression. Variations in parameter values enable the designer to mutate resonance frequencies and mode shape functions as desired. This is particularly important, since the generated energy from a PVEH is significant only if the excitation frequency coming from an external source matches the resonance (natural) frequency of the harvester structure. In subsequent sections of this work, the oscillator mass and spring stiffness are considered as the design parameters to maximize the harvestable voltage and effective frequency bandwidth, respectively. For the optimization, a genetic algorithm is adopted to find the optimal values. Since the voltage frequency response function cannot be implemented in a computer algorithm script, a suitable function approximator (regressor) is designed using fuzzy logic and neural networks. The voltage function requires manual assistance to find the resonance frequency and cannot be done automatically using computer algorithms. Specifically, to apply the numerical root-solver, one needs to manually provide the solver with an initial guess. Such an estimation is accomplished using a plot of the characteristic equation along with human visual inference. Thus, the entire process cannot be automated. Moreover, the voltage function encompasses several coefficients making the process computationally expensive. Thus, training a supervised machine learning regressor is essential. The trained regressor using adaptive-neuro-fuzzy-inference-system (ANFIS) is utilized in the genetic optimization procedure. The optimization problem is implemented, first to find the maximum voltage and second to find the maximum widened effective frequency bandwidth, which yields the optimal oscillator mass value along with the optimal spring stiffness value. As there is often no control over the external excitation frequency, it is helpful to design an adaptive energy harvester. This means that, considering a specific given value of the excitation frequency, energy harvester system parameters (oscillator mass and spring stiffness) need to be adjusted so that the resulting natural (resonance) frequency of the system aligns with the given excitation frequency. To do so, the given excitation frequency value is considered as the input and the system parameters are assumed as outputs which are estimated via the neural network fuzzy logic regressor. Finally, an experimental setup is implemented for a simple pure cantilever energy harvester triggered by impact excitations. Unlike the theoretical section, the experimental excitation is considered to be an impact excitation, which is a random process. The rationale for this is that, in the real world, the external source is a random trigger. Harmonic base excitations used in the theoretical chapters are to assess the performance of the energy harvester per standard criteria. To evaluate the performance of a proposed energy harvester model, the input excitation type consists of harmonic base triggers. In summary, this dissertation discusses several case studies and addresses key issues in the design of optimized piezoelectric vibration-based energy harvesters (PVEHs). First, an advanced model of the integrated systems is presented with equation derivations. Second, the proposed model is decomposed and analyzed in terms of mechanical and electrical frequency response functions. To do so, analytic-numeric methods are adopted. Later, influential parameters of the integrated system are detected. Then the proposed model is optimized with respect to the two vital criteria of maximum amount of extractable voltage and widened effective (operational) frequency bandwidth. Corresponding design (influential) parameters are found using neural network fuzzy logic along with genetic optimization algorithms, i.e., a soft computing method. The accuracy of the trained integrated algorithms is verified using the analytical-numerical closed-form expression of the voltage function. Then, an adaptive piezoelectric vibration-based energy harvester (PVEH) is designed. This final design pertains to the cases where the excitation (driving) frequency is given and constant, so the desired goal is to match the natural frequency of the system with the given driving frequency. In this response, a regressor using neural network fuzzy logic is designed to find the proper design parameters. Finally, the experimental setup is implemented and tested to report the maximum voltage harvested in each test execution
    corecore