Hydrogen is a promising future fuel to enable the transition of transportation sector toward carbon neutrality. The direct utilization of H₂ in internal combustion engines (ICEs) faces three major challenges: high NO_x emissions, severe pressure rise rates, and pre-ignition at mid to high loads. In this study, the potential of H₂ combustion in a truck-size engine operated in spark ignition (SI) and pre-chamber (PC) mode was investigated. To mitigate the high pressure rise rate with the SI configuration, the effects of three primary parameters on the engine combustion performance and NO_x emissions were evaluated, including the compression ratio (CR), the air–fuel ratio, and the spark timing. In the simulations, the severity of the pressure rise was evaluated based on the maximum pressure rise rate (MPRR). Lower compression ratios were assessed as a means to mitigate the auto-ignition while enabling a wider range of engine operation. The study showed that by lowering CR from 16.5:1 to 12.5:1, an indicated thermal efficiency of 47.5% can be achieved at 9.4 bar indicated mean effective pressure (IMEP) conditions. Aiming to restrain the auto-ignition while maintaining good efficiency, growth in λ was examined under different CRs. The simulated data suggested that higher CRs require a higher λ, and due to practical limitations of the boosting system, λ at 4.0 was set as the limit. At a fixed spark timing, using a CR of 13.5 combined with λ at 3.33 resulted in an indicated thermal efficiency of 48.6%. It was found that under such lean conditions, the exhaust losses were high. Thus, advancing the spark time was assessed as a possible solution. The results demonstrated the advantages of advancing the spark time where an indicated thermal efficiency exceeding 50% was achieved while maintaining a very low NO_x level. Finally, the optimized case in the SI mode was used to investigate the effect of using the PC. For the current design of the PC, the results indicated that even though the mixture is lean, the flame speed of H₂ is sufficiently high to burn the lean charge without using a PC. In addition, the PC design used in the current work induced a high MPRR inside the PC and MC, leading to an increased tendency to engine knock. The operation with PC also increased the heat transfer losses in the MC, leading to lower thermal efficiency compared to the SI mode. Consequently, the PC combustion mode needs further optimizations to be employed in hydrogen engine applications.

An optimized active pre-chamber geometry was obtained by combining computational fluid dynamics (CFD) and machine learning (ML). A heavy-duty engine operating with methane under lean conditions was considered. The combustion process was modeled with a multi-zone well-stirred reactor (MZ-WSR) with a skeletal methane oxidation mechanism. The simulations were run for a complete cycle. For the optimization study, the pre-chamber was parametrized; six independent and three dependent variables were considered, while the volume was kept constant. Three hundred pre-chamber designs were generated, and a one-shot design of experiments (DoE) optimization was first considered. A merit function was adopted to rank the designs, and an optimum design was found from the DoE results, which yielded considerable improvements in merit ranking, considering fuel consumption, engine-out emissions, noise, and safety; secondly, machine learning algorithms were trained by utilizing the DoE results aiming at finding a globally optimum geometry for the considered operating condition. Five sequential iterations were performed, and the ML algorithms were capable of proposing a new design with superior performance compared to the best DoE.