报告时间：9月4日（星期三）9:30
报告地点：信息楼以诚为本赢在信誉9001cc310报告厅
报 告 人：Youguang Guo，澳大利亚悉尼科技大学教授
报告题目：Advanced material application and system-level multi-discipline optimization on Electric
Motors and Drives
内容简介：Electric motors and drive systems play a key role in modern industry and domestic applications. This talk aims to present some research activities and ideas at the Center for Electrical Machines and Power Electronics (CEMPE), University of Technology Sydney (UTS). The focus will be the advanced material application and system-level multi-discipline optimization, which are considered as the crucial issues for developing high-performance electric drive systems. The talk also tries to explain the significance, innovation and urgency of these topics.
报告人简介：Youguang Guo was awarded the Bachelor of Engineering degree from Huazhong University of Science and Technology (HUST) in 1985, the Masters of Engineering degree from Zhejiang University in 1988, and the PhD degree from University of Technology Sydney (UTS) in 2004, all in electrical engineering. From 1988 to 1998, he was an associate lecturer/lecturer in the Department of Electric Power Engineering, HUST. From 1998 to 2000 he was a visiting research fellow in the Faculty of Engineering, UTS. From 2004 to 2007 he worked as a postdoctoral research fellow in the Centre for Electrical Machines and Power Electronics, UTS. Since 2008 he has been an academic (lecturer/senior lecturer/associate professor) with the Faculty of Engineering and Information Technology, UTS. He has been an IEEE senior member since 2006; PhD supervisor since 2009. His research interests include measurement and modelling of soft magnetic materials, design and optimization of novel electrical machines, analysis of electromagnetic field in electromagnetic devices, motor drives and control, etc. In these areas, he has published 2 books, 5 book chapters, 267 journal articles and 212 conference papers. 198 of the journal articles are SCI-indexed. His publications have been cited about 4,700 times and his H-index is 33 according to Scopus.
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