Effect of Oil Viscosity and Driving Mode on Oil Dilution and Transient Emissions Including Particle Number in Plug-In Hybrid Electric Vehicle 2020-01-0362
Plug-in electric vehicle (PHEV) has a promising prospect to reduce greenhouse gas (GHG) emission and optimize engine operating in high-efficiency region. According to the maximum electric power and all-electric range, PHEVs are divided into two categories, including “all-electric PHEV” and “blended PHEV” and the latter provides a potential for more rational energy distribution because engine participates in vehicle driving during aggressive acceleration not just by motor. However, the frequent use of engine may result in severe emissions especially in low state of charge (SOC) and ahead of catalyst light-off. This study quantitatively investigates the impact of oil viscosity and driving mode (hybrid/conventional) on oil dilution and emissions including particle number (PN). Two cycles, WLTC (World-wide Harmonized Light Duty Driving Test Cycle) and continuous ECE 15 (European Driving Cycle), were adopted and initial SOC was controlled in the range of 10-13%, which can induce more engine start events. Oil dilution is detected through method of ASTM D3525-04 to identify dilution rate under different conditions. Results show that both in WLTC and ECE 15, frequent engine start will causes high PN and unburned hydrocarbon emissions while NOx is substantially reduced due to relatively low engine loads except in first cold start. Intermittent engine start also significantly accelerates dilution rate but this rate for 5W-30 increases more rapidly than 0W-20 does in hybrid driving mode. Moreover, 5W-30 oil increases fuel consumption due to higher friction work compared to 0W-20 does and the emission of PN along with NOx and THC is also increased.
Citation: Fan, Q., Wang, Y., Xiao, J., Wang, Z. et al., "Effect of Oil Viscosity and Driving Mode on Oil Dilution and Transient Emissions Including Particle Number in Plug-In Hybrid Electric Vehicle," SAE Technical Paper 2020-01-0362, 2020, https://doi.org/10.4271/2020-01-0362. Download Citation
Qinhao Fan, Yunfei Wang, Jianhua Xiao, Zhi Wang, Weizi Li, Tian Jia, Bin Zheng, Robert Taylor