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The Effects of Injection Strategies on Particulate Emissions from a Dual-Injection Gasoline Engine
Technical Paper
2019-01-0055
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
European standards have set stringent PN (particle number) regulation (6×1011 #/km) for gasoline direct injection (GDI) engine, posing a great challenge for the particulate emission control of GDI engines. Dual-injection, which combines direct-injection (DI) with port-fuel-injection (PFI), is an effective approach to reduce particle emissions of GDI engine while maintaining good efficiency and power output. In order to investigate the PN emission characteristics under different dual-injection strategies, a DMS500 fast particle spectrometer was employed to characterize the effects of injection strategies on particulates emissions from a dual-injection gasoline engine. In this study, the injection strategies include injection timing, injection ratio and injection pressure of direct-injection. The experimental results indicated that as the fuel percentage of direct-injection decreased, engine-out particle emissions also gradually declined, with the port-fuel-injection mode yielding the lowest PN emissions. There existed a turning point of direct-injection pulse width, by which the particulate emission characteristics of dual-injection were divided into two different parts. The best direct injection timing in the dual-injection mode to minimize PN emissions was closer to the exhaust top dead center than that in the direct-injection mode. Similar to gasoline-direct-injection, increasing direct-injection pressure in the dual-injection mode also yielded notable reductions in particle number, particle mass and geometry mean diameter (GMD). The experimental results in this paper provide important references for the development and calibration work of dual-injection gasoline engines.
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Chen, W., Xia, C., Mao, K., Tao, J. et al., "The Effects of Injection Strategies on Particulate Emissions from a Dual-Injection Gasoline Engine," SAE Technical Paper 2019-01-0055, 2019, https://doi.org/10.4271/2019-01-0055.Data Sets - Support Documents
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