Semiconductor Power Module Current Balancing Using Reinforcement Machine Learning

B. Westmoreland, A. V. Bilbao, S. B. Bayne

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In high power applications, semiconductor power modules containing paralleled MOSFETs are often used to achieve high output currents. The current distribution between devices within a module is influenced by several factors such as component layout, minor defects due to manufacturing tolerances, and general devices degradation that occurs over time. This paper describes a method of balancing the current between paralleled MOSFETs by independently modulating each device's gate-to-source voltage and measuring the corresponding drain-to-source currents. To achieve this, a detailed simulation is created using MATLAB and Simulink. A reinforcement learning agent is implemented with the goal of adaptively balancing power module current as the components inside degrade over time.

Original languageEnglish
Title of host publication2021 IEEE Pulsed Power Conference, PPC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665433471
DOIs
StatePublished - 2021
Event2021 IEEE Pulsed Power Conference, PPC 2021 - Denver, United States
Duration: Dec 12 2021Dec 16 2021

Publication series

NameIEEE International Pulsed Power Conference
Volume2021-December
ISSN (Print)2158-4915
ISSN (Electronic)2158-4923

Conference

Conference2021 IEEE Pulsed Power Conference, PPC 2021
Country/TerritoryUnited States
CityDenver
Period12/12/2112/16/21

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