In many countries across the world, fossil fuels, especially petroleum, are the largest energy source for powering the socio-economic system, and the transportation sector dominates the consumption of petroleum in these societies. As the petroleum price continuously climbs and the threat of global climate changes becomes more evident, the world is now facing critical challenges in reducing petroleum consumption and exploiting alternative energy sources. A massive adoption of plug-in electric vehicles (PEVs), especially battery electric vehicles (BEVs), offers a very promising approach to changing the current energy consumption structure and diminishing greenhouse gas emissions and other pollutants. Understanding how individual electric vehicle drivers behave subject to the technological restrictions and infrastructure availability and estimating the resulting aggregate supply–demand effects on urban transportation systems is not only critical to transportation infrastructure development, but also has determinant implications in environmental and energy policy enactment. This paper presents an equilibrium-based analytical tool for quantifying travel choice patterns in urban transportation networks with both gasoline and electric vehicular flows. Specifically, a network equilibrium problem with combined destination, route and parking choices subject to the driving range limit and alternative travel cost composition associated with BEVs are formulated, solved, and numerically analyzed under different network settings and scenarios. The defined problem introduces a new dimension of modeling network equilibrium problems with side constraints. The practical significance of the developed tool lies in its solution tractability and extension capability and its ease of being embedded into the existing urban travel demand forecasting framework.