Stochastic Optimal Control for Series Hybrid Electric Vehicles
- ORNL
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.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Transportation Research Center (NTRC)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOE Laboratory Directed Research and Development (LDRD) Program
- DOE Contract Number:
- DE-AC05-00OR22725
- OSTI ID:
- 1068735
- Resource Relation:
- Conference: The 2013 American Control Conference, Washington D.C., DC, USA, 20130617, 20130619
- Country of Publication:
- United States
- Language:
- English
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