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Distributed optimal energy consumption control of HEVs under MFG-based speed consensus

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Abstract

This paper investigates a distributed optimal energy consumption control strategy under mean-field game based speed consensus. Large scale vehicles in a traffic flow is targeted instead of individual vehicles, and it is assumed that the propulsion power of vehicles is hybrid electric powertrain. The control scheme is designed in the following two stages. In the first stage, in order to achieve speed consensus, the acceleration control law is designed by applying the MFG (mean-field game) theory. In the second stage, optimal powertrain control for minimizing energy consumption is obtained through coordinate the engine and the motor under the acceleration constraint. The simulation is conducted to demonstrate the effectiveness of the proposed control strategy.

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Acknowledgements

The authors would like to thank Prof. Minyi Huang of School of Mathematics and Statistics, Carleton University, Canada and Prof. Bing-Chang Wang of School of Control Science and Engineering, Shandong University, China for their creative discussion on mean-field game theory.

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Correspondence to Qiaobin Fu.

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This work was supported in part by Toyota Motor Corporation, Japan.

Qiaobin FU received his M.Sc. degree from School of Mathematical Sciences, Dalian University of Technology, China in 2019. He is currently a Ph.D. candidate of the Department of Engineering and Applied Sciences, Sophia University, Tokyo, Japan. His research interests include optimization, optimal control, mean-field games and mean-field type control theory.

Fuguo XU received the M.E. degree in Control Engineering from Yanshan University, China, in 2016, and the Ph.D. degree in Mechanical Engineering from Sophia University, Japan in 2019. Since 2019, he has been a postdoctoral fellow with the Department of Engineering and Applied Sciences, Sophia University. His research interests include optimal control and applications in powertrain system of hybrid electric vehicles.

Tielong SHEN is a Full Professor in control engineering at Sophia University, Tokyo, Japan. He received his Ph.D. degree in Mechanical Engineering from Sophia University in 1992 and joined Sophia University as Assistant Professor with tenure in April 1992, where he is currently chairing the Shen Laboratory. His research interests include control theory and applications in automotive powertrain systems, power systems, and mechanical systems. In 2005, his laboratory founded a transient control engine testbench and started long-term academic-industrial collaborative research on advanced engine control technology with Toyota Automotive Corporation. Dr. Shen has authored/co-authored eleven text books and has published more than 200 research papers in major peer reviewed journals. He has served SICE, TCCT of CAA, IFAC and IEEE as Chair/Vice-Chair, including General Chair of SICE & CCC 2015 and IPC Chair of IFAC AAC 2016 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.

Kenichi TAKAI is a Full Professor in Department of Mechanical Engineering at Sophia University, Tokyo, Japan. He received his Ph.D. degree from Waseda University in 1996 and joined Sophia University as Assistant Professor with tenure in 1999, where he is currently chairing the Kenichi TAKAI Laboratory. His research interests include Hydrogen trap energy control.

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Fu, Q., Xu, F., Shen, T. et al. Distributed optimal energy consumption control of HEVs under MFG-based speed consensus. Control Theory Technol. 18, 193–203 (2020). https://doi.org/10.1007/s11768-020-0021-6

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  • DOI: https://doi.org/10.1007/s11768-020-0021-6

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