Browse Publications Technical Papers 2018-01-1685
2018-09-10

Improving Combustion and Emission Characteristics in Heavy-Duty Natural-Gas Engine by Using Pistons Enhancing Turbulence 2018-01-1685

Compressed Natural Gas (CNG), because of its low cost, high H/C ratio, and high octane number, has great potential in automotive industry, especially for heavy-duty commercial vehicles. However, relative slow flame speed of natural gas leads to long combustion duration and low thermal efficiency and tends to cause knock combustion at high load, which will aggravate engine thermal load and reliability. Enhancing turbulence intensity in combustion chamber is an effective way to accelerate flame propagation speed and improve combustion performance. In this study, the flow simulations of several piston bowls with different inner-convex forms were carried out using three-dimensional computational fluid dynamics (3D-CFD) software CONVERGE. The numerical results showed the piston bowls with inner-convex could disturb the charge swirl motion and enhance turbulence of different intensity. A hexagram geometry bowl was proved to have the best function in strengthening turbulence intensity. Hence then the combustion processes were calculated based on the original and hexagram bowl. The simulation results suggested hexagram bowl enabled faster burning-rate than original bowl. Lastly, the comparative experiments were conducted at 1000 rpm and 6.5, 12 and 15 bar indicated mean effective pressure (IMEP) loads between the hexagram piston and original piston in the single-cylinder natural-gas engine. The test results indicated the hexagram piston presented approximate 1.8% higher indicated thermal efficiency (ITE) and total hydrocarbon (THC) emission reduced by 60% at 15 bar IMEP load lean burn condition compared to the original piston. However, at 6.5 bar IMEP load stoichiometric combustion, the hexagram piston exhibited about 1.5% lower ITE and poorer THC and nitrogen oxide (NOx) emission characteristics than the original piston, which required further optimization to improve in the future research.

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