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Model predictive control for hybrid vehicle ecological driving using traffic signal and road slope information

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Abstract

This paper presents development of a control system for ecological driving of a hybrid vehicle. Prediction using traffic signal and road slope information is considered to improve the fuel economy. It is assumed that the automobile receives traffic signal information from intelligent transportation systems (ITS). Model predictive control is used to calculate optimal vehicle control inputs using traffic signal and road slope information. The performance of the proposed method was analyzed through computer simulation results. Both the fuel economy and the driving profile are optimized using the proposed approach. It was observed that fuel economy was improved compared with driving of a typical human driving model.

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Author information

Authors and Affiliations

  1. School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo Henan, 454000, China

    Kaijiang Yu & Junqi Yang

  2. School of Information Science and Electrical Engineering, Kyushu University, Fukuoka Fukuoka, 8190395, Japan

    Daisuke Yamaguchi

Authors
  1. Kaijiang Yu
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  2. Junqi Yang
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  3. Daisuke Yamaguchi
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Corresponding author

Correspondence to Kaijiang Yu.

Additional information

This work was supported by National Natural Science Foundation of China (Nos. 51405137, 61403129), the Key Scientific Research Program of the Higher Education Institutions of Henan Province (No. 15A470014), the Program for Innovative Research Team of Henan Polytechnic University, and the Doctoral Program Foundation of Henan Polytechnic University.

Kaijiang YU received his Ph.D. degree from Kyushu University in Electrical and Electronic Engineering, Japan, in 2013. He is currently a lecturer of College of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China. His research interests include HEV energy management and model predictive control.

Junqi YANG received his Ph.D. degree in Control Theory and Control Engineering from Tongji University, Shanghai, China, in 2013. He is currently a lecturer of College of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China. His current research interests include the areas of state estimation, model-based fault detection, and fault-tolerant control.

Daisuke YAMAGUCHI received his M.E. degree from the Department of Electrical Engineering, Kyushu University, Japan, in 2011. His research interests include receding horizon control and its applications.

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Yu, K., Yang, J. & Yamaguchi, D. Model predictive control for hybrid vehicle ecological driving using traffic signal and road slope information. Control Theory Technol. 13, 17–28 (2015). https://doi.org/10.1007/s11768-015-4058-x

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  • DOI: https://doi.org/10.1007/s11768-015-4058-x

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