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For electric vehicle (EV) operations, a major concern for the customers is whether the available charge in the on-board battery pack could sustain a specific trip or not. Within foreseeable future, the charging infrastructure will still remain relatively short. The time for battery charging is also significant longer compared to that for filling gasoline tank. It is thus of practical benefit for EV operation to predict the battery energy demand for a specific trip a prior. In this paper, we present a trip-specific scheme for estimating the battery SOC change based on the trip information from GIS and ITS traffic data. In particular, this study incorporates the stochastic nature of traffic data. For the EV battery pack, the probabilistic change of battery SOC can thus be estimated throughout the spatial domain by combining the stochastic driving cycle, vehicle propulsion dynamics and battery dynamics.