Generalized Analysis Method for Magnetic Energy Harvesters
Large-scale deployment of low-power sensing and computing units calls for unique power management solutions to overcome the inconvenience, costs, and waste problems associated with batteries. Energy harvesting offers an exciting solution to the battery problem, enabling circuits that can power thems...
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Veröffentlicht in: | IEEE transactions on power electronics 2022-12, Vol.37 (12), p.15764-15773 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Large-scale deployment of low-power sensing and computing units calls for unique power management solutions to overcome the inconvenience, costs, and waste problems associated with batteries. Energy harvesting offers an exciting solution to the battery problem, enabling circuits that can power themselves on-site from available ambient energy. Magnetic energy harvesters (MEHs), configured as current transformers, extract energy from the magnetic fields surrounding current-carrying power lines. As maximum power harvest occurs when a magnetic core is on the verge of saturation or saturated to some degree, modeling of magnetic energy harvesters is inherently difficult and nonlinear. This article proposes generalized analytical methods for modeling magnetic energy harvester behavior and validates these methods along with existing circuit model techniques. Intuition for core saturation behavior is presented and agreement with existing models is discussed. The analysis is motivated by addressing the feasibility of a split core magnetic energy harvester to power a microcontroller unit, and the models are experimentally validated for multiple harvester cores. |
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ISSN: | 0885-8993 1941-0107 |
DOI: | 10.1109/TPEL.2022.3195149 |