Search Results

In this work, we conduct a sensitivity analysis of the mean-value internal combustion engine exergy-based model, recently developed by the authors, with respect to different driving cycles, ambient temperatures, and exhaust gas recirculation rates. Such an analysis allows to assess how driving conditions and environment affect the exergetic behavior of the engine, providing insights on the system’s inefficiency. Specifically, the work is carried out for a military series hybrid electric vehicle.

Gasoline direct-injection (GDI) engine technology improves vehicle fuel economy while decreasing CO2 emissions. The main drawback of GDI technology is the increase in particulate emissions compared to the commonly used port fuel injection technologies. Today’s adopted strategy to limit such emissions relies upon the use of aftertreatment gasoline particulate filters (GPFs). GPFs reduce particulates resulting from fuel combustion. Soot oxidation (also known as regeneration) is required at regular intervals to clean the filter, maintain a consistent soot trapping efficiency, and avoid the formation of soot plugs in the GPF channels. In this paper, starting from a multiphysics GPF model accounting for mass, momentum, and energy transport, a sensitivity analysis is carried out to choose the best mesh refinement, time step, and relative tolerance to ensure a stable numerical solution of the transport equations during regeneration while maintaining low computational time.