Effects of Methanol–Ammonia Blending Ratio on Performance and Emission Characteristics of a Compression Ignition Engine

Abstract

Sustainable ammonia is one of the leading candidates in the search for alternative clean fuels for marine applications. This paper aims to build a simulation model of a six-cylinder, four-stroke diesel engine to investigate the effects of increasing the ammonia proportion in methanol–ammonia fuel blends on engine performance and emissions. In the present study, the conditions of different speeds and different proportions of ammonia in fuel blends are investigated. The results show that the average effective pressure, brake power, and brake torque increase by about 5% with an increased ammonia substitution ratio. In terms of economic performance, the changes under medium and low speed conditions are not obvious. However, the change in high speed conditions is significant. The brake specific fuel consumption (BSFC) is reduced by 6.6%, and the brake thermal efficiency (BTE) is increased by 4%. It is found that the performance of the engine is best at medium speed. The best performance is achieved with higher efficiency and lower emissions. The present results can provide guidance for the optimization of ammonia–methanol blends and their applications in engines.

Ammonia Can be Currently Considered as one of the Best Green Energy Ally

“…Hydrogen has also been widely studied as an ignition promoter when testing compression ignition engines, but also methanol, ammonia nitrite, and diesel fuel (n-heptane in simulation runs) [199][200][201][202]. Although modifications in fuel injection strategies are needed, ammonia-diesel dual fuel engines may reduce CO2 emissions by 90% and NOx emissions by 70% compared with original diesel engines [203].…”

Influence of the non-equal aligned nozzles for fuel injection inside the supersonic combustion chamber

“…In the quest for improved fuel efficiency and reduced emissions, the automotive industry has been continuously exploring innovative technologies [14][15][16] . One such technology that has gained significant attention is the multi-injector for efficient fuel mixing in internal combustion engines.…”

Fault Diagnosis of a Multistage Centrifugal Pump Using Explanatory Ratio Linear Discriminant Analysis

“…In intelligent FD, after preprocessing the vibration spectrum, extraction and preprocessing of features are crucial [ 32 ]. Extracting discriminant statistical features from the VS across the time domain, frequency domain, and TFD is essential [ 33 , 34 , 35 , 36 ]. Deep-learning techniques show considerable potential for extracting and classifying features related to faults [ 37 , 38 , 39 ].…”