In this paper, an electronically controlled diesel engine fueled with Fischer-Tropsch fuel was selected to optimize soot and NO emissions. First, the effects of injection parameters on exhaust performance and combustion properties were studied on an engine test bench and then a prediction model based on a support vector machine (SVM) was established according to the test results. On this basis, a decision analysis of soot and NO solutions assigned with different weights was performed based on the TOPSIS analysis method. It turned out that the "trade-off" relation between soot and NO emission was improved effectively. As a matter of fact, the Pareto front selected by this method showed a significant decline compared with the original operating points, in which soot declined by 3.7-7.1% and NO declined by 1.2-2.6%. Finally, the experiments were used to confirm the validity of the results, which indicated that the Pareto front corresponded well with the test value. The maximum relative error between the soot Pareto front and the measured value is 8% while it is 5% for NO emission, and the values of soot and NO under various conditions are more than 0.9. This instance proved that research on diesel engine emission optimization based on the SVM and NSGA-II is feasible and valid.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10268618PMC
http://dx.doi.org/10.1021/acsomega.2c07465DOI Listing

Publication Analysis

Top Keywords

diesel engine
12
pareto front
12
injection parameters
8
engine fueled
8
fueled fischer-tropsch
8
fischer-tropsch fuel
8
soot
6
multi-optimization injection
4
parameters emissions
4
emissions diesel
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!