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

Authors:
Kaijiang Yu;Masakazu Mukai;Taketoshi Kawabe
Affiliations:
Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan 819-0395;Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan 819-0395;Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan 819-0395
Venue:
Artificial Life and Robotics
Year:
2012

Citing 2
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Predictive energy management of a power-split hybrid electric vehicle

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A continuation/GMRES method for fast computation of nonlinear receding horizon control

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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.