Vibrational Energy Harvesting : Design, Performance and Scaling Analysis
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Low-power requirements of contemporary sensing technology attract research on alternate power sources that can replace batteries. Energy harvesters function as power sources for sensors and other low-power devices by transducing the ambient energy into usable electrical form. Energy harvesters absorbing the ambient vibrations that have potential to deliver uninterrupted power to sensing nodes installed in remote and vibration rich environments motivate the research in vibrational energy harvesting. Piezoelectric bimorphs have been demonstrating a pre-eminence in converting the mechanical energy in ambient vibrations into electrical energy. Improving the performance of these harvesters is pivotal as the energy in ambient vibrations is innately low. The present work is organized in three major sections: firstly, audit of the energy available in a vibrating source and design for effective transfer of the energy to harvesters, secondly, design of vibration energy harvesters with a focus to enhance their performance, and lastly, identification of key performance metrics influencing conversion efficiencies and scaling analysis for MEMS harvesters. Typical vibration levels in stationary installations such as surfaces of blowers and ducts, and in mobile platforms such as light and heavy transport vehicles, are determined by measuring the acceleration signal. The frequency content in the signal is determined from the Fast Fourier Transform. A method of determining the energy associated with the vibrating source and the associated power using power spectral density of the signal is proposed. Power requirements of typical sensing nodes are listed with an intent to determine the adequacy of energy harvesting. Effective transfer of energy from a given vibration source is addressed through the concept of dynamic vibration absorption, which is a passive technique for suppressing unintended vibrations. Optimal absorption of energy from a vibration source entails the determination of absorber parameters such as resonant frequency and damping. We propose an iterative method to obtain these parameters for a generic case of large number of identical vibration absorbers resembling harvesters by minimizing the total energy absorbed by the system. The proposed method is verified by analysing the response of a set of cantilever absorber beams placed on a vibrating cantilever plate. We find, using our method, the values of the absorber mass, resonant frequency and damping of the absorber at which significant amount of energy supplied to the system flows into the absorber, a scenario which is favourable for energy harvesting. We emphasize through our work that monitoring energies in the system and optimizing their flow is both rational and vital for designing multiple harvesters that absorb energy from a given vibration source optimally. Enhancing the performance of piezoelectric energy harvesters through a multilayer and, in particular, a multistep configuration is presented. Partial coverage of piezoelectric material in steps along the length of a cantilever beam results in a multistep piezoelectric energy harvester. We find that the power generated by a multistep beam is almost twice of that generated by a multilayer harvester made out of the same volume of polyviny-lidine fluoride (PVDF), further corroborated experimentally. Improvements observed in the power generated prove to be a boon for weakly coupled, low pro le, piezoelectric materials. Thus, in spite of the weak piezoelectric coupling observed in PVDF, its energy harvesting capability can be improved significantly by using it in a multistep piezoelectric beam configuration. Besides, the effect of piezoelectric step length and thickness in a piezoelectric unimorph harvester and performance metrics such as piezoelectric coupling factor and efficiency of conversion are presented. Modeling of a hybrid energy harvester composed of piezoelectric and electromagnetic mechanisms of energy conversion motivated by the need to determine the contribution of each domain to the power generated by the harvester is presented, particularly, when multiple domains exist in a single harvester. Two exclusive schemes of energy transduction are represented using equivalent circuits, which allow modeling any additional transduction scheme employed in the hybrid harvester with relative ease. Furthermore, a method of determining optimal loads in the respective domains using the equivalent circuit of the hybrid harvester is presented. Four different hybrid energy harvesters were fabricated and evaluated for their performance in comparison with that estimated from the proposed models. Additionally, scaling laws for hybrid energy harvesters are presented. The power developed by both piezoelectric and electromagnetic domains is observed to decrease with width and length cubed. Power indices and figures of merit in a hybrid harvester are proposed and are used to estimate the efficiencies of the four fabricated hybrid harvesters. The important design parameters for micro scale harvesting are identified by performing scaling analysis on MEMS piezoelectric harvesters. Performance of energy harvesters is directly related to the harvester attributes, viz., size, material, and end-mass. Depending on the contribution from each attribute, the power developed by MEMS harvesters can vary widely. A novel method of delineating the power developed by a harvester using five exclusive factors representing scaling, composition, inertia, material, and power (SCIMP) factors is presented. Although the proposed method can be extended to bi-morph and multilayer harvesters, in the present work, we elucidate it by applying it to a MEMS unimorph. We also present a unique coupling factor that ensures maximum power factor in a harvester. As any tiny increment in the power generated would considerably improve the power densities of MEMS harvesters, we focus on enhancing the power developed by maximizing each of the five exclusive factors irrespective of material and size. Furthermore, we demonstrate the competence of the proposed method by applying it on nine different MEMS harvesters reported in the literature. Considering the close match between the reported and predicted performance, we emphasize that monitoring the proposed factors is sufficient to attain the best performance from a harvester.
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