Material equivalence, modeling and experimental validation of a piezoelectric boot energy harvester

Feng Qian, Tian Bing Xu, Lei Zuo

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

This paper presents a material equivalent model, electromechanical coupling finite element (FE) modeling and experimental validation of a piezoelectric energy harvester for energy harvesting from human walking. The harvester comprises of six piezoelectric stacks within force amplification frames (FAFs) sandwiched between two heel-shaped aluminum plates, which can be put inside shoes as a shoe heel. The harvester amplifies the vertical dynamic reaction forces with ground at a heel and transfers them to the inner piezoelectric stacks to maximize the power output. Symmetries in geometry, load and boundary conditions are fully exploited and the multilayered piezoelectric stack is simplified as an equivalent bulk to simplify the FE model and expedite dynamic analysis. Dynamic simulation is performed on the symmetric FE model over different external resistive loads with the measured forces at different walking speeds as inputs. The prototype of the harvester is fabricated and tested on a treadmill to validate the proposed material equivalent model and FE model. The simulation results agree well with both the experimental measurements and numerical predictions from the simplified single degree-of-freedom model. Parametric study is performed on the validated FE model to investigate the effect of geometric dimensions of the FAFs on the power output. The peak power outputs of 83.2 and 84.8 mW, and average power outputs of 8.5 and 9.3 mW are experimentally achieved at the walking speeds of 2.5 mph (4.0 km h-1) and 3.0 mph (4.8 km h-1), which agree well with the simulations. Simulation shows that an average power of 34.7 mW can be obtained at 6.0 mph (9.7 km h-1).

Original languageEnglish (US)
Article number075018
JournalSmart Materials and Structures
Volume28
Issue number7
DOIs
StatePublished - Jun 6 2019

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Civil and Structural Engineering
  • Atomic and Molecular Physics, and Optics
  • General Materials Science
  • Condensed Matter Physics
  • Mechanics of Materials
  • Electrical and Electronic Engineering

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