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The requirements set for the next-generation powertrain systems (e.g. performance and emissions) are becoming increasingly stringent with ever-shortening time-to-markets at reduced costs. To remain competitive automotive companies are progressively relying on model-driven development and virtual testing. Virtual test benches, such as HiL (Hardware-in the-Loop) simulators, are powerful tools to reduce the amount of physical testing and speed up engine software calibration process. The introduction of these technologies places new, often conflicting demands (such as higher predictability, faster simulation speed, and reduced calibration effort) upon simulation models used at HiL test benches. The new models are also expected to offer compliance to industry standards, performance and usability to further increase the usage of virtual tests in powertrain development.

Selective Catalytic Reduction (SCR) of NOx through injection of Urea-Water-Solution (UWS) into the hot exhaust gas stream is an effective and extensively used strategy in internal combustion engines. Even though actual SCR systems have 95-96% de-NOx efficiency over test cycles, real driving emissions of NOx are a challenge, proving that there is room for improvement. The efficiency of the NOx conversion is highly dependent on the size of UWS droplets and their spatial distribution. These factors are, in turn, mainly determined by the spray characteristics and its interaction with the exhaust gas flow. The main purpose of this study is to numerically investigate the sensitivity to the modelling framework of the evaporation and mixing of the spray upstream of the catalyst. The dynamics of discrete droplets is handled through the Lagrangian Particle Tracking framework, with models that account for droplet breakup and coalescence, turbulence effects, and water evaporation.