Model predictive control of a power-split hybrid electric vehicle system

Kaijiang Yu, Masakazu Mukai, Taketoshi Kawabe

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

This paper presents a model predictive control approach for the energy management problem of a power-split hybrid electric vehicle system. The model predictive control is suggested to optimally share the road load between the engine and the battery. By analyzing the configuration of the power-split hybrid electric vehicle system, we developed a simplified model for better implementation of model predictive control. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results showed that the fuel economy was better using the model predictive control approach than the ADVISOR rule-based approach in three cases. We conclude that the model predictive control approach is effective for the application of power-split hybrid electric vehicle systems energy management and has the potential for real-time implementation. The simplified modeling method of the power-split hybrid electric vehicle system configuration can be applied to other configurations of hybrid electric vehicle.

Original languageEnglish
Pages (from-to)221-226
Number of pages6
JournalArtificial Life and Robotics
Volume17
Issue number2
DOIs
Publication statusPublished - Dec 1 2012

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Biochemistry, Genetics and Molecular Biology(all)

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