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Minimizing HEV fuel consumption using model predictive control

Authors: Poowanart Poramapojana; Bo Chen;

Minimizing HEV fuel consumption using model predictive control

Abstract

This paper studies the minimization of the fuel consumption of hybrid electric vehicles (HEV) using model predictive control (MPC) method. The presented MPC-based controller calculates an optimal sequence of control inputs to the vehicle plant over the receding prediction horizon based on the torque demand estimated from the desired vehicle speed and the desired state of charge (SOC) of the battery. The controller is implemented in Simulink using Matlab model predictive control toolbox. The effectiveness of the MPC-based controller is validated by the 2004 Toyota Prius, a power-split HEV. The simulation result presents sound transient response performance and the ability to remain the SOC within a reasonable range.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Average
Top 10%
Average
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