journal article·2022-12-07Open access

Numerical Optimization of the EGR Rate and Injection Timing with a Novel Cavitation Model in a Diesel Engine Fueled with PODE/Diesel Blends

Yanju Wei, Chenyang Zhang, Zengqiang Zhu, Yajie Zhang, Dunqiang He, Shenghua Liu

Applied Sciences· Volume 12· Issue 24

Abstract

Polyoxymethylene dimethyl ether (PODE) is one of the most promising alternative fuels for diesel engines with a high cetane number, high oxygen content, and no C-C bonds. In this paper, a new spray model with a novel cavitation sub-model is adopted in order to create a numerical model suitable for engine simulation fueled with PODE/diesel blends. The effects of the blending ratio, injection timing, and EGR rate on the combustion and emission characteristics are investigated by the simulation. The simulation results show that the self-restoring oxygen properties of PODE can efficiently improve the combustion, causing a higher in-cylinder temperature, and therefore, higher NOx emissions. Additionally, with the increase in the blending ratio, the increase in the oxidation activity of PODE/diesel blends and the improvement of atomization are conducive to reducing soot emissions. Then, the injection timing and EGR rate are optimized. The numerical results suggest that the NOx emissions decrease initially and then increase; however, soot emissions decrease monotonically with the delay of the injection timing. When the volume blending ratio is 15%, the emission performance is best when the injection timing is between 710 °CA and 715 °CA. The increase in EGR rate can effectively reduce the in-cylinder temperature and control the NOx emissions, but the excessive EGR rate leads to higher soot emissions and a deteriorated combustion process. Therefore, an EGR rate in the range of 0.0 to 0.2 has a better comprehensive emission performance from the perspective of controlling both the NOx and soot emissions.
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Research context

OpenAlex topics: Advanced Combustion Engine Technologies · Catalytic Processes in Materials Science · Vehicle emissions and performance

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Funding

National Natural Science Foundation of China · Shaanxi Provincial Key R&D Program

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