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Mathematical Problems in Engineering
Volume 2015, Article ID 318025, 15 pages
Research Article

Model Predictive Control for Connected Hybrid Electric Vehicles

1School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China
2College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, China
3Graduate School of Integrated Frontier Sciences, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 8190395, Japan

Received 25 May 2015; Revised 12 July 2015; Accepted 21 July 2015

Academic Editor: Xiaosong Hu

Copyright © 2015 Kaijiang Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for ; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc.) are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.