Dissertation/Thesis Abstract

Vibration-based electromagnetic energy harvester for low-frequency road traffic
by Masumdar, Salim, M.S., California State University, Long Beach, 2017, 57; 10638807
Abstract (Summary)

In recent times, wireless sensor network (WSN) has played an important role for applications in the biomedical, commercial, and military fields. One of the applications is in intelligent transportation system (ITS), which uses sensors placed under the roads to detect vehicles. Progress in the field of Micro-Electro-Mechanical System (MEMS) has made it possible to make sensors that are small and easy to install, but operate on batteries which need to be replaced on a regular basis. For this reason, an alternative supply of power is necessary to run the sensors more effectively.

This thesis project proposes an idea in which the road vibrations can be used to harvest energy, which will further be used to supply power to the sensors. The concept of electromagnetic induction is applied to convert traffic-induced road vibrations into electrical energy. This project is more focused on getting maximum output from low vibrations by making use of a repulsive stack arrangement of magnets rather than using a single magnet while keeping the size of the energy harvester small. The simulation model of the harvester was designed using Simulink and COMSOL software.

The simulation model takes into consideration the vibration data and gives the output voltage generated by the harvester model. Output voltages for road vibrations occurring at different frequencies were tested. Using a repulsive stack approach provided an increase in output voltage compared to a single magnet approach.

Indexing (document details)
Advisor: Mozumdar, Mohammad
Commitee: Ahmed, Aftab, Kwon, Seok-Chul
School: California State University, Long Beach
Department: Electrical Engineering
School Location: United States -- California
Source: MAI 57/01M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Electrical engineering
Keywords:
Publication Number: 10638807
ISBN: 9780355499926
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