A renewable low-frequency acoustic energy harvesting noise barrier for high-speed railways using a Helmholtz resonator and a PVDF film

By Yuan Wang, Zhu Xin, Tingsheng Zhang, Shehar Bano, Hongye Pan, Lingfei Qi, Zutao Zhang, Yanping Yuan. Applied Energy, 2018

172 citations recorded by the source corpus.

Abstract High-speed railways have received much attention globally in recent years. While high-speed railways bring convenience to people, the environmental costs, such as noise pollution, are assignable, especially in residential areas near the railway. Notably, noise is a regenerative energy resource that can be harvested to generate electricity. Therefore, using noise barriers to simultaneously reduce noise and generate electricity is a meaningful research topic. In this paper, we present a novel renewable acoustic energy harvesting noise barrier using a Helmholtz resonator and a Polyvinylidene Fluoride (PVDF) film to convert the acoustic energy of low-frequency noise from high-speed railways into electricity. The renewable acoustic energy harvesting system scheme mainly consists of four components: a noise collection input module, a sound pressure amplification module, an electricity generator module and a power storage module. The sound pressure is amplified in a Helmholtz resonator, and a PVDF film in the electricity generator module can convert acoustic energy into electric energy. The power storage module stores the electric energy in supercapacitors that power small electronic devices, such as the monitors along the railway. Based on the experiments, one unit of the system can produce an instantaneous maximum output voltage of 74.6 mV at 110 dB (SPL), verifying the efficiency and practicability of the proposed acoustic energy harvesting noise barrier system being applied for renewable energy in high-speed railways.

Subfields: Aerospace Engineering, Mechanical Engineering, Pollution

View Paper: https://www.semanticscholar.org/paper/b2c81230057c8f10f5cb9595351769842367b631

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Mechanical Engineering

  1. Binbin Zhang
  2. Lei Zhang
  3. Weiqing Yang
  4. Long Jin
  5. Zhong Lin Wang

Citations in the corpus