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
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;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7039774