This project examines the problem of optimally splitting driver power demand among the different actuators (i.e., the engine and electric machines) in a plug-in hybrid electric vehicle (PHEV). Existing studies focus mostly on optimizing such PHEV power management for fuel economy, subject to charge sustenance constraints, over individual drive cycles. This work adds three original contributions to this literature. First, it uses stochastic dynamic programming to optimize PHEV power management over a distribution of drive cycles, rather than a single cycle. Second, it explicitly trades off fuel and electricity usage in a PHEV, thereby systematically exploring the potential benefits of controlled charge depletion over aggressive charge depletion followed by charge sustenance. Finally, it examines the impact of variations in relative fuel-to-electricity costs on optimal PHEV power management, for the first time. Our models focus on a single-mode power-split PHEV configuration for mid-size sedans, but the approach is extendible to other configurations as well.