DocumentCode :
2901293
Title :
Stochastic optimal control for series hybrid electric vehicles
Author :
Malikopoulos, Andreas A.
Author_Institution :
Energy & Transp. Sci. Div., Oak Ridge Nat. Lab., Oak Ridge, TN, USA
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
1189
Lastpage :
1194
Abstract :
Increasing demand for improving fuel economy and reducing emissions has stimulated significant research and investment in hybrid propulsion systems. In this paper, we address the problem of optimizing online the supervisory control in a series hybrid configuration by modeling its operation as a controlled Markov chain using the average cost criterion. We treat the stochastic optimal control problem as a dual constrained optimization problem. We show that the control policy that yields higher probability distribution to the states with low cost and lower probability distribution to the states with high cost is an optimal control policy, defined as an equilibrium control policy. We demonstrate the effectiveness of the efficiency of the proposed controller in a series hybrid configuration and compare it with a thermostat-type controller.
Keywords :
Markov processes; air pollution; electric propulsion; fuel economy; hybrid electric vehicles; optimal control; statistical distributions; stochastic systems; thermostats; average cost criterion; controlled Markov chain; dual constrained optimization problem; emission reduction; fuel economy; hybrid propulsion systems; optimal control policy; probability distribution; research and investment; series hybrid electric vehicles; stochastic optimal control problem; supervisory control; thermostat-type controller; Batteries; Engines; Fuels; Hybrid electric vehicles; Optimal control; Probability distribution; System-on-chip;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6579997
Filename :
6579997
Link To Document :
بازگشت