Electromagnetic energy harvesting using magnetic levitation architectures: A review

Pedro Carneiro, Marco P. Soares dos Santos, André Rodrigues, Jorge A.F. Ferreira, José A.O. Simões, A. Torres Marques and Andrei L. Kholkin

Applied Energy, 2020, vol. 260, issue C, No S0306261919318781

Abstract: Motion-driven electromagnetic energy harvesters have the ability to provide low-cost and customizable electric powering. They are a well-suited technological solution to autonomously supply a broad range of high-sophisticated devices. This paper presents a detailed review focused on major breakthroughs in the scope of electromagnetic energy harvesting using magnetic levitation architectures. A rigorous analysis of twenty-one design configurations was made to compare their geometric and constructive parameters, optimization methodologies and energy harvesting performances. This review also explores the most relevant models (analytical, semi-analytical, empirical and finite element method) already developed to make intelligible the physical phenomena of their transduction mechanisms. The most relevant approaches to model each physical phenomenon of these transduction mechanisms are highlighted in this paper. Very good agreements were found between experimental and simulation tests with deviations lower than 15%. Moreover, the external motion excitations and electric energy harvesting outputs were also comprehensively compared and critically discussed. Electric power densities up to 8 mW/cm3 (8 kW/m3) have already been achieved; for resistive loads, the maximum voltage and current were 43.4 V and 150 mA, respectively, for volumes up to 235 cm3. Results highlight the potential of these harvesters to convert mechanical energy into electric energy both for large-scale and small-scale applications. Moreover, this paper proposes future research directions towards efficiency maximization and minimization of energy production costs.

Keywords: Energy harvesting; Self-powering; Electromagnetic harvesting; Magnetic levitation; Modelling; Design optimization (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (23)

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DOI: 10.1016/j.apenergy.2019.114191

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