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Technical Paper

Improvement of Fuel Consumption for SI Engines by Combining with Glow Plug Heated Sub-Chamber and Lean Burn

2020-11-30
2020-32-2310
In order to get better results in the Formula SAE of Japan, it is necessary to develop a small displacement engine with an ideal fuel consumption rate. Therefore, the authors started to improve an existing engine by combining with glow plug heated sub-chamber and lean burn. Lean burn conditions are usually adopted in gasoline engines, having the advantages of high specific heat ratio, low pump loss, and low cooling loss due to requiring a decreased combustion temperature. The combination of these elements can be expected to vastly improve thermal efficiency and fuel consumption. Unfortunately, however, when the mixture becomes lean, the ignition delay increases, and the flame propagation speed reduces. This leads to an increase in combustion fluctuation. The authors intend to solve this problem by installing a glow plug in a newly designed sub-chamber. This type of device would usually be used to heat the sub-chamber of a diesel engine to solve the cold start problem.
Technical Paper

Improvement of On-board In-cylinder Gas Flow Model and Wall Heat Transfer Prediction Model for CI Engines Using CFD Analysis and PIV Measurements under Motoring and Firing Conditions

2020-01-24
2019-32-0542
For the improvement of the transient driving performance and the thermal efficiency for diesel engines, it is effective to control the fuel injection by model-based control (MBC) on ECU with cycle-by-cycle calculation, and MBC requires six models; gas flow, spray development, mixture formation, combustion, ignition delay, and heat loss. The authors previously developed on-board in-cylinder gas flow and wall heat transfer prediction models to estimate the heat loss. However, the developed gas flow model has an undetermined coefficient called the turbulence intensity coefficient (TIC), which significantly influences the prediction accuracy of the wall heat transfer prediction model. The present study improved the gas flow model and the wall heat transfer prediction model by applying TICs obtained using the PIV and CFD analysis.
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