The H2-ICE project aims at developing, through numerical simulation, a new generation of hybrid powertrains featuring a hydrogen-fueled Internal Combustion Engine (ICE) suitable for 12 m urban buses in order to provide a reliable and cost-effective solution for the abatement of both CO₂ and criteria pollutant emissions. The full exploitation of the potential of such a traction system requires a substantial enhancement of the state of the art since several issues have to be addressed. In particular, the choice of a more suitable fuel injection system and the control of the combustion process are extremely challenging. Firstly, a high-fidelity 3D-CFD model will be exploited to analyze the in-cylinder H2 fuel injection through supersonic flows. Then, after the optimization of the injection and combustion process, a 1D model of the whole engine system will be built and calibrated, allowing the identification of a “sweet spot” in the ultra-lean combustion region, characterized by extremely low NOx emissions and, at the same time, high combustion efficiencies. Moreover, to further enhance the engine efficiency well above 40%, different Waste Heat Recovery (WHR) systems will be carefully scrutinized, including both Organic Rankine Cycle (ORC)-based recovery units as well as electric turbo-compounding. A Selective Catalytic Reduction (SCR) aftertreatment system will be developed to further reduce NOx emissions to near-zero levels. Finally, a dedicated torque-based control strategy for the ICE coupled with the Energy Management Systems (EMSs) of the hybrid powertrain, both optimized by exploiting Vehicle-To-Everything (V2X) connection, allows targeting H2 consumption of 0.1 kg/km. Technologies developed in the H2-ICE project will enhance the know-how necessary to design and build engines and aftertreatment systems for the efficient exploitation of H2 as a fuel, as well as for their integration into hybrid powertrains.

This paper investigates, through computational fluid dynamics (CFD) simulations, the knock resistance improvements that can be obtained in a turbo-charged GDI engine with water injection. In a first step, water and gasoline injector models are validated comparing the results with experimental data from constant volume chamber tests. Then, multi-cycle simulations are performed using the G-equation turbulent combustion model focusing on spray evolution and wall film dynamics. The main intent is analyzing the effectiveness of different water injection timings and injection pressures in a port water injection (PWI) installation. Combustion rates are validated against experimental engine data, with and without water injection. Afterwards, in order to predict autoignition behavior with different spark advance (SA) timings, the extended coherent flamelet model (ECFM) combined with a tabulated kinetic ignition (TKI) dataset is used. End-gas autoignition delays are calculated using a reduced mechanism for toluene primary reference fuel (TPRF), which revealed essential for capturing actual gasoline ignition characteristics. Results indicate that the water atomization quality, i.e., injection pressure, is significant in a PWI installation allowing a reduction of the water wall film formation in the ports. Water injection timing needs also to be carefully chosen for optimized performance. As the injected water allows the SA to be increased, the overall benefits on indicated mean effective pressure and fuel consumption are quantified under the same knock safety margin, matching adequately well the available measurements.

Multi-cycle large-eddy simulations (LES) are performed to investigate combustion cycle-to-cycle variability (CCV) in a gasoline spark ignited optical access engine operating under homogeneous stoichiometric conditions. Combustion is addressed with the Thickened Flame Model (TFM) and finite rate chemistry is accounted for through a reduced oxidation reaction mechanism. In view of the fact that computational costs of LES engine simulations are still very high today, this work investigates the use of adaptive mesh refinement (AMR) in the flame zone in conjunction with the artificial flame thickening applied by the TFM model. The paper discusses how the resulting coupled TFM-AMR combustion model allows good resolution of the flame, maintaining accuracy at acceptable costs. First, the details of the coupled model are presented and the effects of the parameters are explored, highlighting their impact on the combustion prediction. Then, computational fluid dynamics (CFD) simulation results are validated against experimental data collected in a low-speed low-load engine point, by comparing 20 LES cycles and 100 measured cycles, for mass fraction burned, combustion phasing, flame images and CCV indices. Lastly, a detailed investigation on the fastest and slowest numerical cycles is presented, analyzing instantaneous flame structures, ignition behaviors, propagation speeds, and probability density function (PDF) of the instantaneous velocity fluctuation around the spark region. The results show that combustion variability is highly correlated to the resolved velocity field and the resolved turbulence intensity, which is found to be the main cause of CCV and affects the early flame kernel growth. This work is an early attempt to use TFM-AMR combustion model for LES simulations of internal combustion engines.

With the aim of expanding the knowledge on liquid ammonia sprays, this paper investigates the injection process of ammonia through Computational Fluid Dynamics (CFD) using the Lagrangian particle method, within the Reynolds Averaged Navier Stokes (RANS) approach for turbulence modeling. Numerical results and experimental data are compared in terms of liquid and vapor tip penetration, local values of Sauter Mean Diameter (SMD) and global spray morphology. This model validation process allows to build a predictive simulation framework for ammonia injection. In order to explore also the flash boiling phenomenon, results of CFD simulations of ammonia spray and the comparison with experimental data are presented for different conditions, ranging from non-flashing regimes to flash boiling conditions. Breakup model constants need to be markedly tuned for each regime, and established values for traditional fuels, like gasoline, appear not to work well with ammonia. Ultimately, this study highlights that capturing spray local details (such as local SMD values) across all the regimes with a single model or setup is still challenging, especially with a new fuel such as ammonia, whose properties differ by a large amount from more established values for hydrocarbons.