Title: Toward Rel-world Driving Energy Optimization via On-board Powertrain Control with the Connectivity
Abstract:
For the electrified powertrains, big potential for improving energy efficiency via dynamical system optimization techniques has been shown in the last few decades. However, at the industrial mass production level, the optimization techniques have not been widely commercialized. A bottleneck in practical application of energy optimization strategies is the prediction of driver’s power-demand, since once we formulate the energy saving problem as a dynamics-constraint optimization, the power-demand during the targeted optimization period plays the role of strong constraint of the power generation. To solve this optimization problem, it must be previously known. However, uncertainty and stochasticity in the driver’s behavior and the environment make it difficult in the real-world driving scenarios. This talk focuses on this issue. Benefit from the connected environment, learning the driver’s and the traffic behavior enables us to predict the power-demand and use it to construct real-time optimization algorithm. In this talk, challenges in real-world driving optimization will be explained firstly, and several research experiences in V2X-based prediction, mean-field limitation approach to modeling traffic behavior will be introduced. With these fundamental tools, on-board optimization for individual powertrain and broadcasting control targeted a crowd of vehicles will be introduced.
Biography:
Tielong Shen received his PhD degree in Mechanical Engineering from Sophia University, Tokyo, Japan, 1992, and joined Sophia University as Assistant Professor with Tenure in April 1992, where he served as Associate Professor, Professor, Specially-appointed Professor till March of 2024. He is now serving a Chair Professor at School of Control Science and Engineering, Dalian University of Technology, Dalian, China. He is also a Professor Emeritus of Sophia University, and Visiting Professor of Center for Power Source Research for Next-generation Mobility, Chiba University, Japan. His research interests include dynamical system control theory and applications in automotive powertrain systems, power systems, and mechanical systems. Recently, his research is focused on learning and control algorithms, mean-field limitation approach and application in automotive systems. Dr. Shen is the winner of the 8th TCCT Outstanding Contribution Award, and Fellow of The Society of Instrument and Control Engineers (SICE), Japan. He is currently serving Director of SICE.
