Abstract
This paper proposes a two-stage hierarchy control system with model predictive control (MPC) for connected parallel HEVs with available traffic information. In the first stage, a coordination of on-ramp merging problem using MPC is presented to optimize the merging point and trajectory for cooperative merging. After formulating the merging problem into a nonlinear optimization problem, a continuous/GMRES method is used to generate the real-time vehicle acceleration for two considered HEVs running on main road and merging road, respectively. The real-time acceleration action is used to calculate the torque demand for the dynamic system of the second stage. In the second stage, an energy management strategy (EMS) for powertrain control that optimizes the torque-split and gear ratio simultaneously is composed to improve fuel efficiency. The formulated nonlinear optimization problem is solved by sequential quadratic programming (SQP) method under the same receding horizon. The simulation results demonstrate that the vehicles can merge cooperatively and smoothly with a reasonable torque distribution and gear shift schedule.
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This work was supported in part by the Foundation of Japan MEXT Scientific Research-B (KAKENHI) (No. 17H03284), and in part by Toyota Motor Corporation, Japan.
Bo ZHANG received the B.Eng. degree in Electronic Information and Electrical Engineering, and the M.E. degree in Control Theory and Control Engineering from Dalian University of Technology, Dalian, China, in 2014 and 2017. She is currently pursing the Ph.D. degree at Sophia University, Tokyo, Japan. Her research interests include the optimal control strategies and powertrain control.
Wenjing CAO received her Ph.D. degree of Engineering from the Graduate School of Integrated Frontier Science, Kyushu University, Japan, in 2014. After that she joint Nissan Motor Co., Ltd. and worked on powertrain control of CAVs for 4 years. Then she changed her job and is currently an assistant professor in the Department of Engineering and Applied Sciences, Sophia University, Japan. Her research area focuses on control theory and application in motion control of automobile and control of automobile powertrain.
Tielong SHEN received the Ph.D. degree in Mechanical Engineering from Sophia University, Tokyo, Japan, in 1992. He has been a Faculty Member with the Department of Mechanical Engineering, Sophia University, since 1992, where he currently serves as a Professor in the Department of Engineering and Applied Sciences. His research interests include control theory and application in mechanical systems, power systems, and automotive powertrain.
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Zhang, B., Cao, W. & Shen, T. Two-stage on-board optimization of merging velocity planning with energy management for HEVs. Control Theory Technol. 17, 335–345 (2019). https://doi.org/10.1007/s11768-019-9129-y
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DOI: https://doi.org/10.1007/s11768-019-9129-y