To comply with the stringent Euro VI emission standards, two techniques have been proposed for natural gas engines, namely, lean-burn combustion with oxidation catalyst (OC) and stoichiometric combustion with three-way catalyst (TWC). In this paper, comparisons are drawn between the two techniques in terms of carbon monoxide (CO), nitrogen oxides (NOx), and methane (CH4) emissions and fuel economy. The results indicated that the postcatalyst CO emissions of lean-burn combustion with OC are lower, whereas the postcatalyst NOx and CH4 emissions are higher than those of stoichiometric combustion with TWC. This can be explained by the combined effects of lower engine-out CO emissions and higher engine-out NOx and CH4 emissions as well as lower overall conversion efficiency for all emissions with the adoption of lean-burn combustion with OC. Thus, it can be concluded that although the fuel economy of stoichiometric combustion with TWC is inferior to lean-burn combustion with OC, it is still considered ...

Currently, selective catalytic reduction (SCR) systems have become an essential part in diesel engines, and urea crystallization is one of the most serious issues in SCR systems. In this paper, the urea deposit formation processes in the SCR system were investigated by numerical simulations based on a fluid–solid coupling method. The results show that the masses of the wall film and solid urea are larger at conditions with lower temperatures and higher injection rates. At higher temperatures, cyanate ions and ammonium ions are the most predominant compositions in the wall film, while at lower temperatures, solid urea is the main composition. It could also be deduced that the location of urea crystallization is more affected by the design of mixer at higher temperatures, whereas at lower temperatures, the location and installation angle of urea-water solution injector play a more important role.

Adoption of methane scavenged prechamber has been considered as a promising solution to extend the lean limit of large-bore natural gas engines. In this paper, the effects of prechamber energy fraction, Miller cycle, excess air ratio, intake temperature, fuel methane number, and engine load are examined by a full set of experiments and detailed analysis on a single-cylinder large-bore natural gas engine. The results indicate that brake thermal efficiency (BTE) could be improved by increasing prechamber energy fraction, reducing excess air ratio, and using fuel with a higher methane number. It is also observed that brake thermal efficiency is higher at higher engine loads. Moreover, knock intensity is shown to be higher at higher prechamber energy fractions, higher intake temperatures, and lower methane numbers. For a methane scavenged prechamber engine, the cyclic variation of indicated mean effective pressure is maintained at a low level, attributed to the strong ignition energy. However, reducing air excess ratio and utilizing valve timing with a higher Miller degree are capable of reducing cyclic variation to a lower level. Additionally, carbon monoxide (CO) emissions are lower at higher prechamber energy fractions, higher excess air ratios, and lower Miller degree, which first increases and then decreases with the increase of methane number. Hydrocarbon emissions could be controlled by increasing intake temperature, reducing prechamber energy fraction and excess air ratio, and using a higher Miller degree. Meanwhile, lower NOx emissions can be obtained by raising prechamber energy fraction and excess air ratio. It is also deduced that implementation of higher Miller degree has positive effect on NOx reduction.

This paper investigates the problem of real-time parameter identification for ship maneuvering parameters and wave peak frequency in an ocean environment. Based on the idea of Euler discretion, a combined model of ship maneuvering and wave peak frequency (ship–wave) is made a discretion, and a discrete-time auto-regressive moving-average model with exogenous input (ARMAX) is derived for parameter identification. Based on the ideas of stochastic gradient identification and multi-innovation theory, a multi-innovation stochastic gradient (MI-SG) algorithm is derived for parameter identification of the ship–wave discretion model. Maximum likelihood theory is introduced to propose a maximum likelihood-based multi-innovation stochastic gradient (ML-MI-SG) algorithm. Compared to the MI-SG algorithm, the ML-MI-SG algorithm shows improvements in both parameter identification accuracy and identification convergence speed. Simulation results verify the effectiveness of the proposed algorithm.