4.7 Article

Optimum resistance analysis and experimental verification of nonlinear piezoelectric energy harvesting from human motions

期刊

ENERGY
卷 118, 期 -, 页码 221-230

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2016.12.035

关键词

Energy harvesting; Piezoelectric; Nonlinear; Human motion; Optimum load resistance

资金

  1. National Natural Science Foundation of China [51575426, 51421004, 51611530547]
  2. National Key Scientific Instrument and Equipment Development Project [2012YQ03026101]
  3. Novel Energy Materials, Engineering Science and Integrated Systems (NEMESIS) [320963]
  4. Program for New Century Excellent Talents in University [NCET-120453]

向作者/读者索取更多资源

The complex dynamic behavior of nonlinear harvesters make it difficult to identify the optimum mechanical and electrical parameters for maximum output power, when compared to linear energy harvesting devices. In addition, the chaotic and multi-frequencies characteristics of responses under realistic human motion excitations provide additional challenges for enhancing the energy harvesting performance, such as the traditional frequency domain method being inappropriate for optimum resistance selection. This paper provides detailed numerical and experimental investigations into the influence of resistance on the efficiency of nonlinear energy harvesting from human motions. Numerical simulations under human motions indicate that optimum resistance of a nonlinear harvester can be attained to maximize the power output. Moreover, simulations of linear and nonlinear harvesters under harmonic excitations verify the effectiveness of frequency dominant method to obtain optimum resistance in the absence of a change in the dynamic behavior of the harvester. However, numerical simulations and experiments are the effective methods when the harvester shows complex dynamic characteristics. Experimental measurements of harvested power under different motion speeds and resistances are in agreement to the numerical analysis for the nonlinear harvester. The results demonstrate the effectiveness of the proposed resistance optimization method for nonlinear energy harvesting from human motions. (C) 2016 Elsevier Ltd. All rights reserved.

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