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Renaud Gillon

Researcher at ON Semiconductor

Publications -  91
Citations -  777

Renaud Gillon is an academic researcher from ON Semiconductor. The author has contributed to research in topics: Equivalent circuit & MOSFET. The author has an hindex of 14, co-authored 89 publications receiving 715 citations.

Papers
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Journal ArticleDOI

Self-heating characterization and extraction method for thermal resistance and capacitance in high voltage MOSFETs

TL;DR: In this article, a simple pulsed-gate experiment is proposed and the influence of its parameters (pulse duration and duty factor) are analyzed, and it is demonstrated that in our 100 V DMOSFET, SHE is cancelled by using pulses with duration less than 2 /spl mu/s and duty factors lower than 1:100.
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Compact Modeling of Lateral Nonuniform Doping in High-Voltage MOSFETs

TL;DR: In this article, a detailed analysis and modeling of lateral nonuniform doping present in intrinsic MOS channel of highvoltage (HV) MOSFETs, e.g., vertical (VDMOS) and lateral diffused MOS (LDMOS), is presented.
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Scalable general high voltage MOSFET model including quasi-saturation and self-heating effects

TL;DR: This model includes physical effects like the quasi-saturation, impact-ionization and self-heating, and a new general model for drift resistance, which can be used for any high voltage MOSFET with extended drift region.
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Characterizing the TEM Cell Electric and Magnetic Field Coupling to PCB Transmission Lines

TL;DR: In this article, the authors presented the models of the coupling between the transverse electromagnetic (TEM) field generated in the TEM cell and the arbitrarily oriented microstrip (MS) lines and coplanar waveguides (CPW).
Proceedings ArticleDOI

Bias-dependent drift resistance modeling for accurate DC and AC simulation of asymmetric HV-MOSFET

TL;DR: In this paper, a detailed investigation of the drift resistance evolution with the gate and drain biases in Lateral DMOS architectures is performed using the concept of intrinsic drain voltage, V/sub K/, applied to both simulated and measured data.