Modeling wireless acoustic power transmission systems
Choi, Jae Won
Loading…
Permalink
https://hdl.handle.net/2142/107851
Description
Title
Modeling wireless acoustic power transmission systems
Author(s)
Choi, Jae Won
Issue Date
2020-02-05
Director of Research (if dissertation) or Advisor (if thesis)
Singer, Andrew C
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Acoustic modeling
Abstract
In the presence of a barrier which is conductive and structurally prevents penetration of electromagnetic energy, acoustic wave transmission is often used for data communications and could be a viable option for wireless power transfer. Such a power transfer system design would need to incorporate the behavior of the entire acoustic channel, taking into account the properties of the acoustic transducers that create the acoustic signals, the propagation of the acoustic signals through the barrier, and the transducers and circuitry that transform the acoustic power back into electrical power. The thesis presents a model that translates the acoustic components of the system into a model that is suitable for analysis using the electrical components. Basic principles of acoustic physics and piezoelectric material properties will be discussed. Then an ABCD-parameter, two-port network representation is derived for a system compromising a piezoelectric transducer and a solid barrier. Such representations can be also be expressed in lumped-element circuits, which can be useful in designing the electrical end of the power transfer system. Using ABCD-parameter models, multiple acoustical and piezoelectric elements are cascaded and modeled as a single two-port network. Using parameter conversion of the two-port network, source and load impedance can be matched to maximize the power transfer.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.