Plug-in electric vehicles (PEVs) are a rapidly evolving technology representing a potentially sustainable alternative to traditional internal combustion engine vehicles (ICEVs). By relying on electric power rather than petrol, these new vehicles will require a new infrastructure system for en-route charging options, be that fast charging stations or battery swap stations. PEVs will therefore generate mobile energy demands that must be met by regional power providers. Optimally designing infrastructure to meet these new energy demands will require knowledge of the spatiotemporal travel patterns, which are inherently dependent on the user's activities and travel behaviour. Furthermore, limited battery capacity will result in a distance constraint for PEV drivers, inevitably impacting individual's travel and activity patterns. This constrained behaviour must be incorporated into traditional traffic assignment models, requiring innovative routing algorithms. Previous work by Jiang et al (2012) introduced a novel distance constrained user-equilibrium-based assignment model which allowed charging requirements to be incorporated into the traditional traffic assignment problem. Using Jiang et al.'s assignment model, we evaluate the impact of PEV traveller's en route charging needs on the network system performance under various charging station location options. We identify key scenarios in which infrastructure planning decisions result in sub-optimal network performance, motivating the need for intelligently selecting charging station locations.