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Issue No.05 - May (2011 vol.10)
pp: 669-683
Jaeseok Yun , Georgia Institute of Technology, Atlanta and Korea Electronics Technology Institute, Seongnam
Shwetak N. Patel , University of Washington, Seattle
Matthew S. Reynolds , Duke University, Durham
Gregory D. Abowd , Georgia Institute of Technology, Atlanta
ABSTRACT
We present an empirical study of the long-term practicality of using human motion to generate operating power for body-mounted consumer electronics and health sensors. We have collected a large continuous acceleration data set from eight experimental subjects going about their normal daily routine for three days each. Each subject is instrumented with a data collection apparatus that simultaneously logs 3-axis, 80 Hz acceleration data from six body locations. We use this data set to optimize a first-principles physical model of the commonly used velocity damped resonant generator (VDRG) by selecting physical parameters such as resonant frequency and damping coefficient to maximize the harvested power. Our results show that with reasonable assumptions on size, mass, placement, and efficiency of VDRG harvesters, most body-mounted wireless sensors and even some consumer electronics devices can be powered continuously and indefinitely from everyday motion. We have optimized the power harvesters for each individual and for each body location. In addition, we present the potential of designing a damping- and frequency-tunable power harvester that could mitigate the power reduction of a generator generalized for "average” subjects. We present the full details on the collection of the acceleration data sets, the development of the VDRG model, and a numerical simulator, and discuss some of the future challenges that remain in this promising field of research.
INDEX TERMS
Human power harvesting, inertial generator, optimal design, tunable generator, human-powered device.
CITATION
Jaeseok Yun, Shwetak N. Patel, Matthew S. Reynolds, Gregory D. Abowd, "Design and Performance of an Optimal Inertial Power Harvester for Human-Powered Devices", IEEE Transactions on Mobile Computing, vol.10, no. 5, pp. 669-683, May 2011, doi:10.1109/TMC.2010.202
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