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Burak Ozpineci

Researcher at Oak Ridge National Laboratory

Publications -  174
Citations -  8029

Burak Ozpineci is an academic researcher from Oak Ridge National Laboratory. The author has contributed to research in topics: Inverter & Power electronics. The author has an hindex of 38, co-authored 165 publications receiving 6572 citations. Previous affiliations of Burak Ozpineci include National Transportation Research Center & Federal University of Mato Grosso do Sul.

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Proceedings ArticleDOI

Optimized Renewable Energy Integration for EV High-Power Dynamic Wireless Charging Systems

TL;DR: In this article, an optimization model for renewable energy integration in the DWCS is proposed to mitigate the grid impact and minimize the operation costs of the whole system, and the tradeoff between grid impact mitigation and operation costs minimization, relationships among power demand from power grid, photovoltaic (PV) capacity, wind energy (WE) capacity and energy storage (ES) capacity are analyzed.
Proceedings ArticleDOI

Inductive power harvesting for a touchless transmission line inspection system

TL;DR: A touch-free transmission line inspection system in which an unmanned aerial vehicle (UAV) conducts all inspection activities and, while doing so, charges from the line via inductive power transmission.
Proceedings ArticleDOI

A Novel Three-Phase Oak Ridge AC / DC Converter for Wireless EV Charger Applications

TL;DR: In this paper, a novel three-phase converter is proposed for ac to dc wireless power transfer (WPT) systems for electric vehicle (EV) charging applications, which reduces the design complexity and cost by eliminating the front-end converter stage compared to the conventional systems.
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Anti-series normally-On SiC JFETs operating as bidirectional switches

TL;DR: In this paper, the authors investigate a bidirectional switch formation that is formed by using two normally-on SiC JFETs in anti-series with no anti-parallel diodes.
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Sensor Compensation in Motor Drives using Kernel Regression

TL;DR: In this article, a mathematical solution based on kernel regression is proposed to compensate the measurement error of a faulty sensor, which can generate more accurate and reliable estimates in motor control systems.