A series-Stacked architecture with 4-to-1 GaN-Based isolated converters for high-Efficiency data center power delivery

Yizhe Zhang, Enver Candan, Robert C.N. Pilawa-Podgurski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Series-stacked server power delivery architectures have been proposed recently that can achieve much higher energy efficiency than conventional power delivery architectures. When servers are connected in series, differential power processing (DPP) converters can be used to regulate the server voltages when the servers are consuming different amount of currents. Server-to-bus DPP architecture has unique advantages among several other DPP architectures such as being able to achieve the minimum power processed in the DPP converters, and having a higher reliability than other DPP architectures. This work presents the development of a server-to-bus DPP architecture for server power delivery. The hardware prototype is built with four 4-to-1 isolated DPP converters with GaN switches. Four 12V 120W Dell servers are used in the bench test to validate the operation of server-to-bus DPP. 98.99% efficiency is achieved while the servers are running a real-life data center computational load.

Original languageEnglish (US)
Title of host publication2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4467-4474
Number of pages8
ISBN (Electronic)9781509029983
DOIs
StatePublished - Nov 3 2017
Event9th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2017 - Cincinnati, United States
Duration: Oct 1 2017Oct 5 2017

Publication series

Name2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017
Volume2017-January

Other

Other9th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2017
CountryUnited States
CityCincinnati
Period10/1/1710/5/17

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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