DocumentCode
114874
Title
Multi-time scale model predictive control framework for energy management of hybrid electric vehicles
Author
Josevski, Martina ; Abel, Dirk
Author_Institution
Dept. of Mech. Eng., RWTH Aachen Univ., Aachen, Germany
fYear
2014
fDate
15-17 Dec. 2014
Firstpage
2523
Lastpage
2528
Abstract
In this paper a multi-time scale model predictive control framework is proposed and applied in the efficiency and drivability optimization of hybrid electric vehicles. A multi-layer model predictive control concept simultaneously enables a static optimization over a long prediction horizon and the optimization of the transient system response which leads to better drivability. The proposed control architecture is evaluated on a standard driving cycle and on the example of a parallel hybrid electric vehicle configuration. The obtained simulation results indicate an improved performance of the two layer energy management strategy compared to the case when a single layer model predictive control scheme is applied to optimize the fuel economy of a hybrid electric vehicle. Although the concept has been proven on the example of parallel hybrid electric vehicle it holds in general for any other hybrid configuration as well.
Keywords
energy management systems; hybrid electric vehicles; predictive control; transient response; drivability optimization; efficiency optimization; fuel economy; hybrid configuration; long prediction horizon; multilayer model concept; multitime scale model predictive control framework; parallel hybrid electric vehicle configuration; single layer model scheme; standard driving cycle; static optimization; transient system response; two layer energy management strategy; Batteries; Hybrid electric vehicles; Ice; Predictive control; Torque; Vehicle dynamics;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location
Los Angeles, CA
Print_ISBN
978-1-4799-7746-8
Type
conf
DOI
10.1109/CDC.2014.7039774
Filename
7039774
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