Recent engine development has been mainly driven by increased specific volumetric power and especially by fuel consumption minimization. On the other hand the stringent emission limits require a very fast cold start that can be reached only using tailored catalyst heating strategy.This kind of thermal management is widely used by engine manufactures although it leads to increased fuel consumption. This fuel penalty is usually higher for high power output engines that have a very low load during emission certification cycle leading to very low exhaust gas temperature and, consequently, the need of additional energy to increase the exhaust gas temperature is high.An alternative way to reach a fast light off minimizing fuel consumption increase is the use of an Electrical Heated Catalyst (EHC) that uses mechanical energy from the engine to generate the electrical energy to heat up the catalyst. Following this thermal management strategy the energy input can be tailored according to the component need and the energy loss in the system can be minimized. Moreover, the efficiency of such systems can be further optimized using for example brake energy recuperation or advanced thermal management.The present work describes the different engine management strategies tested by Ferrari to find the best compromise between fuel consumption and emission reduction.

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Nowadays, numerical simulations play an important role during the design and optimization phase of the after-treatment system (ATS). Simulation tools, based on both simple 1D or detailed CFD approaches, are able to describe the chemical species transport through the system and the main reactions occurring in the catalytic devices. In this context, the availability of accurate kinetic schemes is of primary importance for the reliable prediction of the ATS performance. In this work, the theme of the calibration of the reaction scheme based on the available experimental measurement is investigated, with particular interest in the modeling of the three-way catalyst. Hence, a methodology for the calibration is proposed, based on a two-step calibration procedure, which exploits two different types of the experimental data set, namely, oxygen storage capacity tests and standard homologation cycles. The adoption of these two different data sets allows us to optimize separately the kinetics of the reactions occurring at high temperatures and low temperatures, with a specific focus on the oxygen storage mechanism at the basis of the operation of a three-way catalyst. The effectiveness of the developed calibration procedure is finally demonstrated, considering two different test cases.

In order to reduce development costs and time-to market, 1D and 3D CFD tools can support engine design providing reliable estimations of the tailpipe emissions. In particular, 3D-CFD in-cylinder simulations can evaluate formation of both soot and gaseous pollutants inside the combustion chamber. The main issue in such kind of simulations is the validation against experimental findings. In fact, the complexity of the emission measurements does not allow a straightforward one-to-one comparison between numerical and experimental results. Therefore the present paper aims at providing, on the one hand, a robust numerical framework for both gaseous and solid emissions, on the other hand a dedicated post-processing for a fair comparison between simulations and experiments. From a numerical standpoint, a simplified approach is dedicated to gaseous emissions, while a more detailed one is reserved to soot modeling. The latter is based on the Sectional Method, whose reaction rates are tabulated following 0D chemical kinetic simulations of a purposely designed surrogate in a constant pressure reactor. Simulations and experiments proposed in the present analysis are referred to a high-performance turbocharged direct-injection spark-ignition engine operated at part-load and low rpms. On equal performance, revving speed and mean mixture quality, different injection timings are investigated. The developed numerical approach and post-processing ensure a good agreement between simulations and experiments.