The demand for high NOx conversion efficiency and low tailpipe ammonia slip for urea-based selective catalytic reduction (SCR) systems has substantially increased in the past decade, as NOx emission legislations for Diesel engines are becoming more stringent than ever before. Model-based control strategies are fundamental to meet the dual objective of maximizing NOx reduction and minimizing NH3 slip in urea-SCR catalysts. In this paper, a control oriented model of a Cu-zeolite urea-selective catalytic reduction (SCR) system for automotive diesel engines is presented. The model is derived from a quasi-dimensional four-state model of the urea-SCR plant. In order to make it suitable for the real-time urea-SCR management, a reduced order one-state model has been developed, with the aim of capturing the essential behavior of the system with a low computational demand. The model estimates the relevant species (i.e. NO, NO2 and NH3) independently. The ability to target NH3 slip is important not only to minimize urea consumption but also to reduce this unregulated emission. The feature to discriminate between NO and NO2 is important for two reasons: firstly the NOx reduction is highly promoted by the NO2 based reactions; secondarily, NO2 is more toxic than NO for both environment and human health. Parameters identification and model validation have been performed vs. simulation data achieved by a commercial code of the SCR system, based on the four-state quasi-dimensional modeling approach. The accuracy of the reduced-order model is demonstrated by comparing NO, NO2 and NH3 concentrations with those simulated by the more complex reference model. It is observed that the one state model allows estimating the SCR behavior with satisfactory accuracy to be used for model-based control of urea-SCR systems.