• WeChat official account for the department
    WeChat official account for undergraduate students of the department
    WeChat official account for graduate students of the department
    WeChat official account for alumni of the department
    WeChat official account for the Energy Internet Research Institute, Tsinghua University
    WeChat official account for the Sichuan Energy Internet Research Institute, Tsinghua University

清华大学电机系

清华大学电机系本科生

清华大学电机系研究生

清华大学电机系校友会

清华大学能源互联网创新研究院

People & Viewpoints

Current Location: Home > News > People & Viewpoints > Content

报告题目:Influence of Driving Patterns and Optimal Powertain Combined Design and Control on Plug-in Electric Vehicle

报 告 人:Dr. Orkun Karabasoglu

Assistant Professor, Sun Yat-sen University-Carnegie Mellon University Joint Institute

Associate Professor, Sun Yat-sen University, CHN

时间:2015年7月11日 上午10:00-11:30

地点:清华大学电机系西主楼3区102室

联系人:陆海峰

报告人简介:Dr. Karabasoglu received his Ph.D and M.Sc. in Mechanical Engineering from Carnegie Mellon University (CMU) in 2013. Later on, he worked at Massachusetts Institute of Technology (MIT) as a postdoctoral research associate in Mechatronics Research Laboratory. Currently, he is an assistant professor in Electrical and Computer Engineering at Sun Yat-sen University-Carnegie Mellon University Joint Institute of Engineering and SYSU-CMU Shunde International Joint Research Institute. He is the founder and director of Intelligent Vehicles and Energy Systems Laboratory. He also works as an associate professor in Mobile Information Engineering at Sun Yat-sen University.

报告摘要:Energy and environment are two of the major concerns of our century. This seminar is about my efforts on making electrified vehicles cost competitive for a green and sustainable future. Driving patterns and powertrain control strategy affect the cost and environmental benefits of plugin hybrid electric vehicles (PHEVs).

I investigate the impact of driving patterns on life cycle cost and emissions of PHEVs compared to other powertrain technologies.

(2) To minimize the impact of driving patterns, I develop a robust combined optimal powertrain design and control framework.

(3) Using this framework, I show that it is possible to downsize expensive batteries with GPS-assisted predictive controllers.

—— Share ——

Previous:Global Power & Energy Internet: Is It Real?

Next:Beyond Technology: Improving Energy Efficiency through Social-Psychological Approaches

Close