Considering the trade-off relationship between brake specific fuel consumption (BSFC), combustion noise (CN) and NOx emission, it is a difficult task to optimize them simultaneously in a marine diesel engine. In order to overcome this problem, a novel genetic algorithm and improved chicken swarm optimization (GA-ICSO) hybrid algorithm was proposed, where the enhanced Levy flight and adaptive self-learning factor were introduced in this algorithm. Computational comparisons between GA-ICSO and other effective optimization algorithms were performed using four standard test functions, validating the improvements in both accuracy and stability for GA-ICSO. Furthermore, a predictive engine model based on a phenomenological approach was developed and validated. This model coupled the proposed algorithm for the optimization of a marine diesel engine. In the optimization process, five control parameters were selected as design variables, including injection timing (IT), intake cam phasing (ICP), intake valve closing (IVC), intake temperature and pressure. Results show that, a lower objective value can be obtained by GA-ICSO than other widely used optimization algorithms for all the operating conditions. Besides, by comparing the results between the optimal generations and baselines, it could be found that, under the condition of 50%, 75% and 100%load, CN is reduced by 10.7%, 4.9% and 3.9%, NOx is decreased by 15%, 31% and 33%, and BSFC is suppressed by 10.8%, 13.3% and 9.5%, respectively. Finally, heat release rates, noise spectrums, cylinder pressures and temperatures were all employed to discuss the optimization results of a marine diesel engine under different working conditions.

Pilot injection combined with exhaust gas recirculation (EGR) is usually utilized to realize the partially premixed compression ignition (PPCI) mode in diesel engines, which enables the simultaneous decrease of nitrogen oxide and soot emissions to satisfy emission regulations. Moreover, the ignition delay of main injection combustion can also be shortened by pilot injection, and then combustion noise is reduced. Nevertheless, the mechanisms of pilot injection impacts on combustion noise are not completely understood. As such, it is hard to optimize pilot injection parameters to minimize combustion noise. Therefore, experiments were conducted on a four-stroke single-cylinder diesel engine with different pilot injection strategies and 20% EGR as part of an investigation into this relationship. Firstly, the combustion noise was analyzed by cylinder pressure levels (CPLs). Then, the stationary wavelet transforms (SWTs) and stationary wavelet packet transform (SWPT) were employed to decompose in-cylinder pressures at different scales, and thus the combustion noise generated by pilot and main combustion was investigated in both the time and frequency domain. The results show that pilot injection is dominant in the high frequency segment of combustion noise, and main injection has a major impact on combustion noise in the low and mid frequency segment. Finally, the effects of various pilot injection parameters on suppressing combustion noise were analyzed in detail.