Haoyang You, Han Wang, Jayanth Reddy Regatti, Jon Hall, Alec Schnabel, Boxue Hu, Julia Zhang, Abhishek Gupta, Jin Wang
{"title":"Intelligent Health Monitoring System Hardware Design for Paralleled Devices with Fast Dv/dt Output","authors":"Haoyang You, Han Wang, Jayanth Reddy Regatti, Jon Hall, Alec Schnabel, Boxue Hu, Julia Zhang, Abhishek Gupta, Jin Wang","doi":"10.1109/IEMDC47953.2021.9449599","DOIUrl":null,"url":null,"abstract":"With the increasing power rating of wide bandgap (WBG) devices in parallel, the system reliability encounters unprecedented challenges. Artificial intelligence (AI) methods could be introduced to monitor device health conditions and realize intelligent control for each device. In this paper, an intelligent health monitoring system is designed for the future AI implementation for paralleled devices with a fast dv/dt output. The detailed system circuitry and layout are discussed. The proposed system consists of monitoring and control functions. For the monitoring function, a measurement board is designed to capture the device temperature, turn on and turn off drain-to-source voltage, drain-to-source current. For the control function, a gate drive board is shown with the ability to select various gate voltage and gate resistance based on the control signals. Experimental verifications are provided at the end.","PeriodicalId":106489,"journal":{"name":"2021 IEEE International Electric Machines & Drives Conference (IEMDC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Electric Machines & Drives Conference (IEMDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMDC47953.2021.9449599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the increasing power rating of wide bandgap (WBG) devices in parallel, the system reliability encounters unprecedented challenges. Artificial intelligence (AI) methods could be introduced to monitor device health conditions and realize intelligent control for each device. In this paper, an intelligent health monitoring system is designed for the future AI implementation for paralleled devices with a fast dv/dt output. The detailed system circuitry and layout are discussed. The proposed system consists of monitoring and control functions. For the monitoring function, a measurement board is designed to capture the device temperature, turn on and turn off drain-to-source voltage, drain-to-source current. For the control function, a gate drive board is shown with the ability to select various gate voltage and gate resistance based on the control signals. Experimental verifications are provided at the end.