Date of Award


Document Type


Degree Name

Master of Science


Department of Operational Sciences

First Advisor

Sarah G. Nurre, PhD.


Optimizing operations at plug-in hybrid electric vehicle (PHEV) battery swap stations is internally motivated by the movement to make transportation cleaner and more efficient. A PHEV swap station allows PHEV owners to quickly exchange their depleted PHEV battery for a fully charged battery. The PHEV-Swap Station Management Problem (PHEV-SSMP) is introduced, which models battery charging and discharging operations at a PHEV swap station facing nonstationary, stochastic demand for battery swaps, nonstationary prices for charging depleted batteries, and nonstationary prices for discharging fully charged batteries. Discharging through vehicle-to-grid is beneficial for aiding power load balancing. The objective of the PHEV-SSMP is to determine the optimal policy for charging and discharging batteries that maximizes expected total profit over a fixed time horizon. The PHEV-SSMP is formulated as a finite-horizon, discrete-time Markov decision problem and an optimal policy is found using dynamic programming. Structural properties are derived, to include sufficiency conditions that ensure the existence of a monotone optimal policy. A computational experiment is developed using realistic demand and electricity pricing data. The optimal policy is compared to two benchmark policies which are easily implementable by PHEV swap station managers. Two designed experiments are conducted to obtain policy insights regarding the management of PHEV swap stations. These insights include the minimum battery level in relationship to PHEVs in a local area, the incentive necessary to discharge, and the viability of PHEV swap stations under many conditions.

AFIT Designator


DTIC Accession Number