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学术报告
Prof. Tielong Shen 学术报告会
作者:发布时间:2019-12-16

题目:Real-time Optimization and Control of Automotive Powertrains

时间:2019年12月16日 10:00

地点:bat365在线中国官网登录入口 F210会议室

报告人:Prof. Tielong Shen (Sophia University)

邀请人:王亚飞 副教授(智能汽车研究所)

 

Biography

Tielong Shen is a Full Professor in control engineering at Sophia University, Tokyo, Japan. He graduated from Northeast Heavy Machinery Institute, 1982, and received his PhD degree in Mechanical Engineering from Sophia University 1992, and joined Sophia University as Assistant Professor with Tenure in April 1992, where he is currently chairing Shen Laboratory. His research interests include control theory and applications in automotive powertrain systems, power systems, and mechanical systems. In 2005, his laboratory founded transient control engine testbench and started long-term academic-industrial collaborative research on advanced engine control technology with Toyota automotive Corporation, Japan. He has served SICE, TCCT of CAA, IFAC and IEEE as Chair/vice-chair including General Chair of SICE&CCC2015, IPC Chair of IFAC AAC2016, IFAC ECoSM2018, etc. He is currently a member of the IEEE Technical Committee on Automotive Control and IFAC Technical Committee on Automotive System Control. He is currently serving as General Chair of SICE Annual Conference 2021, and General Chair of IFAC Conference on ECOSM 2021.

 

Abstract

As vehicular propulsion system, energy efficiency is one of the most important issues in developing ECU control algorithms. For modern automotive powertrains such as electrically controlled engines and electrified powertrains, real-time optimal control is a feasible and effective way to improving the energy efficiency. However, the complexity in modeling and uncertainties in practice make it challenging. This talk will begin with a brief overview of challenging issues in real-time optimization of powertrains, and practical applications of engine transient control energy management of hybrid electric vehicles will be introduced with demonstration of experimental validation.

 

 

 

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