Date of Award:
Doctor of Philosophy (PhD)
Electrical and Computer Engineering
Wireless power transfer through inductive coupling, termed as inductive power transfer (IPT), is one of the important technologies in power electronics that enable transfer of power between entities without physical connections. While it has seen significant growth in the areas such as electric vehicle charging, phone charging and biomedical implants, its emerging applications include charging of autonomous underwater vehicles (AUVs) and dynamic charging of electric vehicles from the roadway. This dissertation addresses a few key challenges in these areas of IPT applications, paving the way for future developments.
For the WPT for AUV, the recently developing sea-bed installed marine systems are targeted, which typically gets power from on-shore sources through constant dc low-current distribution. As the present underwater IPT topologies are not suitable for such applications, this dissertation proposes underwater IPT topologies to interface directly with such constant current distribution and provide a constant voltage output supply to the on-board systems inside the AUVs. The considerations for seawater losses and the small-signal models for control purposes are also addressed. Analysis and experimental results are provided for validations of the analytical designs and models.
In the area of electric vehicle dynamic wireless power transfer (EV DWPT), the comparison of control performances of different coupler, compensation topologies and control implementations are addressed. The effect of communication latency on control bandwidth are also addressed. The outcomes are presented through analysis and simulations, and based on that future research recommendations are made to pave way for future commercial developments of well regulated and interoperable EV DWPT systems.
Bagchi, Anindya Chitta, "Emerging Works on Wireless Inductive Power Transfer: AUV Charging from Constant Current Distribution and Analysis of Controls in EV Dynamic Charging" (2020). All Graduate Theses and Dissertations. 7980.
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