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A new hybrid energy harvester for human motion power generation |
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Abstract Converting energy from human motions into usable electricity for powering the operation of sensors is always a hot topic in energy harvesting researches. Yet how to efficiently exploit human motion and improve the level of output power are still key problems to be solved as well as the environmental adaptability. Based on the feature of human walking or running, a new hybrid energy harvester is proposed and designed, with consideration of combining piezoelectric and electromagnetic mechanisms. The piezoelectric energy harvesting is based on the strain of a piezoelectric beam, while the electromagnetic generator employs the configuration of stacked magnetic group cutting the coil. The theoretical model for the hybrid energy harvesting system is constructed to describe the characteristics of output voltage on the base of lumped parameter model. The predicted results are compared with the experimental measurements. The comparison agrees well which indicates the feasibility of the present model. It is found that there are two peaks of output voltage within the excitation frequency region. The results show that these two peaks can be adjusted by varying the length of piezoelectric beam which is related with the nature frequency of energy harvester. In this way, the bandwidth of energy harvesting can be increased when the two peaks are closing to each other according to the excitation frequency in surroundings. In addition, human motion experiments display that the hybrid energy harvester can output high DC voltage in a short time, for instance, when the running speed is 5km/h, 1.1V DV voltage is produced in 3 seconds to drive the sensor to work. When the time length of running is 30 seconds, the sensor can work for 77 seconds by virtue of the hybrid energy harvester. The present hybrid energy harvester has abilities of quick charge and endurance which offers potential applications of charging battery or powering sensors.
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Received: 28 April 2019
Published: 07 November 2019
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