Pollutant Reduction Techniques Used for Nonroad Combustion Ignition Engines

Suratwala, Darshit P.; Harpale, Varsha K.; Khurge, Deepti

doi:10.1007/s40032-022-00899-5

Cited by 1 publication

(1 citation statement)

References 141 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since diesel engines are lean burn, and emit less CO hence it is not considered in the paradigm of optimization in this study. NO x is the major pollutant that count approx to 50% of the total pollutants, second being PM followed by HC 52 therefore NO x , OP and HC are focused in this study. NO x , HC, OP are the regulated emissions and BTE is directly connected to the economy hence these variables are considered as the primary goals of this study, where BTE is to be maximized and pollutants are to be reduced.…”

Section: Methodsmentioning

confidence: 99%

Application of response surface methodology to optimize the emissions and performance of a dual fuel engine using diesel and dimethyl ether

Kumar

Yadav

2023

Env Prog and Sustain Energy

View full text Add to dashboard Cite

In this study, the combustion and exhaust emission characteristics of a single‐cylinder, water‐cooled, four‐stroke VCR engine at a fixed CR were evaluated using DME and diesel with timed manifold injections of 2, 3, 4, and 5 ms for DME and conventional diesel settings. The investigational trials showed that DME has the capability to reduce NOx and OP while used in an optimized range and to have clean combustion characteristics. Induction of DME under low to medium load conditions resulted in a reduction in NOx, OP, and BTE with an increase in HC, whereas at higher load settings, NOx increased with an increase in diesel energy share. The dual fuel combustion was characterized by a short ignition delay, an early start of combustion, and increased in‐cylinder pressure due to the increased compression work input during the cycle. The absence of carbon–carbon bonds in DME molecules caused low soot emissions during dual fuel combustion. After experimentation, RSM was applied to the results for parametric optimization and found to be a useful tool for reducing the error as well as minimizing the number of trials. The optimum settings were achieved at 2 kW load and 4 ms duration, where the desirability function reached a value of 0.94189. The regression equations developed by the model were validated by 9 random experiments, and the error is found to be acceptable. The engine should be operated at medium load to control NOx, and the DME energy share should be low and near 50%.

show abstract

Section: Methodsmentioning

confidence: 99%