Plug-in hybrid electric vehicles (PHEVs) have rechargeable energy storage which can be used to run the vehicle on shorter range on electricity from the grid. In the absence of a priori information about the trip, a straightforward strategy is to first deplete the battery down to a minimum level and then keep the state of charge (SoC) around this level. However, largely due to the battery losses, the overall fuel economy can be improved if the battery is discharged gradually. This requires some a priori knowledge about the trip.This paper investigates the tradeoff between improved fuel economy and the need for a priori information. This investigation is done using a variant of telemetry equivalent consumption minimization strategy (T-ECMS) which is modified to be used for a PHEV. To implement this strategy, several parameters need to be tuned based on an assumption of the future trip. By studying two different levels of details, the tradeoff between fuel economy and a priori information is evaluated. It is shown that the proposed strategy improves the fuel economy considerably even when general information is available. However, increase in the details of the a priori information improves the fuel economy even further.