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Ayan Mallik

Researcher at University of Maryland, College Park

Publications -  50
Citations -  726

Ayan Mallik is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Power factor & Voltage regulation. The author has an hindex of 14, co-authored 28 publications receiving 456 citations.

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Bi-Directional CLLC Converter With Synchronous Rectification for Plug-In Electric Vehicles

TL;DR: In this paper, an innovative technique for synchronous rectification in a bidirectional CLLC converter with an integrated transformer for plug-in electric vehicle applications is presented and simulated using finite element analysis.
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Control of a Three-Phase Boost PFC Converter Using a Single DC-Link Voltage Sensor

TL;DR: In this paper, the authors proposed a new methodology to control a three-phase boost power factor correction (PFC) using a single dc output voltage sensor, which uses the ripple information of the measured dc-link voltage, converter dynamics, and switching states at a preceding sample in order to estimate the present state of four unknown state variables and, thus, establishes the control method.
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Variable-Switching-Frequency State-Feedback Control of a Phase-Shifted Full-Bridge DC/DC Converter

TL;DR: In this article, the authors presented a methodology to control a phase-shifted full-bridge (PSFB) dc/dc converter with variable switching frequency, as a function of the output load power.
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Input Voltage Sensorless Duty Compensation Control for a Three-Phase Boost PFC Converter

TL;DR: In this paper, the authors proposed an input voltage sensorless control algorithm for three-phase active boost rectifiers, where the input ac-phase voltages can be accurately estimated from the fluctuations of other measured state variables and preceding switching state information from converter dynamics.
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Modeling and Optimization of an Integrated Transformer for Electric Vehicle On-Board Charger Applications

TL;DR: The proposed approach includes a comprehensive transformer loss model with accurate electromagnetic description of leakage inductance and optimization process, and a multiobjective optimization using genetic algorithm to optimize the performance-space variables.