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 language | English |
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Pages (from-to) | 221-226 |
Number of pages | 6 |
Journal | Artificial Life and Robotics |
Volume | 17 |
Issue number | 2 |
DOIs | |
Publication status | Published - Dec 2012 |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Biochemistry, Genetics and Molecular Biology(all)