Low Cost Optimization of Engine Emissions for an Intake Runner Designed for Medium Capacity CI Engine through Correlations between Emission Values and Intake Configurations 2016-01-1004

The energy crisis coupled with depleting fuel reserves and rising emission levels has encouraged research in the fields of performance enhancement, emission reduction technologies and engineering designs. The present paper aims primarily to offset the problem of high emissions and low efficiencies in low cost CI engines used as temporary power solutions on a large scale. The investigation relates to the low cost optimization of an intake runner having the ability to vary the swirl ratio within the runner. Test runs reveal that NOx and CO₂ follow a relatively smaller gradient of rise and fall in their values depending on the configuration; whereas UHC and CO have a rapid changes in values with larger gradients. However, in a relative analysis, no configuration was able to simultaneously reduce all emission parameters and thus, there exists a necessity to find an optimized configuration as a negotiation between the improved and deteriorated parameters. This arrangement would enable to find a reduced BSFC with an optimized emission parameter without adding any overhead costs for emission reduction techniques and push the potential of current technologies to meet the stringent emission norms. Rigorous data collection was performed which helped to establish a mathematical relation between the configuration and the emission parameter values taken one at a time. Thus, a mathematical relation by basic curve fitting technique on a commercial mathematical software was established and optimized for a set of discrete load values. In addition to the optimization process, the analysis also helps understand and determine a practical correlation between swirl parameters and engine emissions for engineering applications. Since the design is capable of changing configurations during engine running operations, the applicability is enhanced for all load values if sufficient data is determined and the process is repeated.