Numerical Investigations of Innovative SI engines suitable for hybrid powertrains with reduced CO2

The problem of atmospheric air pollution, caused by the Internal Combustion Engines (ICEs), has never been greater than today. Car manufacturers, driven by more and more stringent legislations, are continuously forced to find proper technical solutions to deal with this challenge, without giving up on the high standards regarding engine performance. In particular, the new emission limit for the CO2 recently set for the 2026, with a target of 80 g/km of CO2 along the WLTC, has never pushed so much the automotive manufacturers in developing innovative and clean solutions to improve the fuel economy of the vehicle fleets. However, how to solve this problem is still an open debate. On the one hand, the complete disappearance in few years of the ICE-based propulsion systems in the automotive sector, replaced by fuel cell and/or Battery Electric Vehicles (BEVs) seems to be expected. On the other hand, several analyses declare that potential benefits of a BEV cannot be easily defined. Indeed, if the CO2 formed during the entire vehicle life cycle is considered, the emissions from the two antagonist vehicles become comparable, to such an extent that ICE-based vehicles could be even better than the “zero-emission” alternatives. As often happen, the truth is somewhere in-between, hence, it should be expected in the years to come rather than a pure electric or ICE-based mobility a scenario characterized by variegated technologies that are best suited to the contest in which they are employed. This means that ICE-based vehicles, HEVs, PHEVs, BEVs or even Fuel Cell based vehicles, will coexist in the market for a long time, pushing car manufactures to overcome the limits related to each technology. On the light of the above concerns, the topic of this research activity is to numerically investigate, through a hierarchical simulation-level approach, innovative SI engines, eventually suitable for hybrid powertrains, with a strongly reduced CO2 impact. To this aim, two different ICEs are analyzed, assessing their CO2 emission along the WLTC. The former is a downsized turbocharged VVA 2-cylinder engine, for a conventional vehicle application, defining the reference for the state of art of ICE-based propulsion system. The latter is an innovative 4-cylinder SI engine, equipped with an active pre-chamber ignition system, which guarantees an ultra-lean operation all over the engine operating range. Here, HEV/PHEV architectures are considered for the vehicle simulation. Additionally, the potential fuel economy as well as CO2 benefits, coming from Connected and Automated Vehicles (CAV), are investigated through a numerical methodology able to benchmark these last on a real world-scenario. The simulation efforts carried out to assess the previous objectives is mainly effected in a 0D/1D modelling environment, where the whole engine system is schematized through a network of 1D pipes and 0D cylinders, the latter described in term of in-house developed quasi-dimensional models of the in-cylinder phenomena. In particular, the flame propagation in the conventional engine is modeled according to a well-assessed version of the fractal combustion model developed at the University of Naples Federico II. Whereas, for the pre-chamber engine, a dedicated and innovative procedure, still based on the fractal theory, is developed, since, differently from conventional SI ICEs, only a few predictive combustion models were available in the current literature at the beginning of this activity. The reliability of the overall simulation models is checked for both the engines through the comparisons with 3D or experimental data, using a unique engine-dependent set of tuning constants. Once verified that the physics included in the model is accurate enough to guarantee a good agreement, the model is utilized as a predictive tool for deriving the complete performance maps of both a conventional and a pre-chamber engine. To this aim, a Rule-Based (RB) calibration strategy is also implemented in both the models to identify the optimal values of each control variable in whole operating plane. Of course, the reliability of the RB calibration is demonstrated, too, through the comparison with the outcomes of a general-purpose optimizer, for both the engine architectures. The RB methodology demonstrates to furnish control parameter close to the optimizer, in a very limited computational time. Finally, the engine maps are embedded in vehicle simulations to quantify the CO2 emission over a WLTC, for many different engine and vehicles architectures. In parallel to the above activities, a dedicated off-line Energy Management Strategy, named ETESS, for the HEV is also developed aiming to minimize the CO2 emission along a prescribed mission. The ETESS is compared with the well-known Pontryagin Minimum Principle (PMP) in terms of management of the control units and vehicle performance outcomes. Although the ETESS can only furnish a sub-optimal solution, the reduced computational time to the respect of the PMP suggests the possibility to implement it for an on-line application, with limited penalization. The results carried out in this research activity show that the ICE-based system can reach 94.81g/km CO2 along the WTLC. However, this value is still far away from the EU target of 80 g/km CO2 of 2026. On the contrary, PHEV architecture combined with a pre-chamber engine, able to achieve a maximum Indicted Thermal Efficiency (ITE) around 50%, attains a CO2 emission equal to 43.0 g/km along the same regulatory driving cycle. Although this impressive result, it has to remark that in the current regulation the CO2 emissions necessary for charging the battery is not included, leading to a not representative enough results of the real condition. On the contrary, the HEV configuration reaches 88.8 g/km CO2, very close to the EU ambitious target, suggesting that the combination of these two technologies could be a suitable solution for the years to come. Additionally, connected and autonomous vehicle, thanks to the possibility to use the look-ahead information from the route can further improve the CO2 reduction of about 15-17%, respect to a vehicle not equipped with this technology