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Title: Centralized Stochastic Optimal Control of Complex Systems

Conference ·
OSTI ID:1185343

In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Transportation Research Center (NTRC)
Sponsoring Organization:
USDOE Laboratory Directed Research and Development (LDRD) Program
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1185343
Resource Relation:
Conference: 2015 European Control Conference, Linz, IL, Austria, 20150715, 20150717
Country of Publication:
United States
Language:
English

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