Wearable Piezoelectric Energy Harvesting From Human Gait: Modeling and Experimental Validation

IEEE SENSORS JOURNAL(2022)

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Abstract
Wearable devices with a flexible and stretchable form factor enable novel and attractive applications. The promising outlook for these devices is hindered by their limited battery capacity constrained by size and other physical limitations. Motion energy harvesting can alleviate these challenges and reduce dependency on batteries. Despite this potential, a definitive capacity for wearable motion energy harvesting has yet to be identified. To facilitate the exploration of this capacity, we propose an analytical model for the energy harvesting potential of a wearable piezoelectric energy harvester placed on the knee joint. In addition, we validate the proposed model extensively with a prototype piezoelectric energy harvester. Our results show that the proposed model estimates the harvested power with less than 5% mean absolute percentage error for all gait speeds and various transducer configurations. In addition, the proposed harvester can generate 161 mu W power at 5 mph. We further show that this amount can sustain a 35 mu A load.
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Key words
Analytical modeling,edge computing,energy harvesting,IoT,piezoelectric,wearable device
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