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Combined Benefits of Variable Valve Actuation and Low-Pressure EGR on SI Engine Efficiency Part 1: Part Load
Technical Paper
2019-01-0241
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Modern spark ignited engines face multiple barriers to achieving higher thermal efficiency. This study investigated the potential of utilizing both continuously variable valve actuation (VVA) and low-pressure cooled exhaust gas recirculation (EGR) to improve engine thermal efficiency at part-load conditions. Six speed / load points were investigated on a 1.6 L turbocharged gasoline direct injection engine. A design of experiment (DoE) approach using the Box-Behnken surface response model was conducted. The DoE results revealed different brake specific fuel consumption (BSFC) responses to the valve phasing and the intake valve lift at different operating conditions. Further engine testing was carried out at each speed / load point to confirm the engine efficiency and combustion performance when targeting different valvetrain controls and EGR strategies. The results indicated that utilizing the VVA system could always reduce BSFC at the studied operating conditions. The BSFC reduction was attributed to reduced pumping and incomplete combustion losses. The reduction in losses was attributed to optimizing the amount of hot trapped residuals compared with the fixed valve configuration, and load control through valve phasing and lift and thus de-throttling the engine. The cooled EGR offered further BSFC reduction benefits from the perspective of reducing in-cylinder heat losses provided the combustion stability limit was not exceeded. Additionally, the EGR played an important role for cases where the hot trapped residuals decreased by large amount due to the reduced overlap and increased intake pressure requirement with reduced intake valve lift.
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Wang, Y., Conway, G., and Chadwell, C., "Combined Benefits of Variable Valve Actuation and Low-Pressure EGR on SI Engine Efficiency Part 1: Part Load," SAE Technical Paper 2019-01-0241, 2019, https://doi.org/10.4271/2019-01-0241.Data Sets - Support Documents
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