Modeling the Effects of the Ignition System on the CCV of Ultra-Lean SI Engines using a CFD RANS Approach
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- Provide download link
- Format
- Price
- Non-members (tax incl.)：￥6,600 Members (tax incl.)：￥5,280
- Paper/Info type
- SAE Paper
No.2021-01-1147
- Pages
- 1-10(Total 10 p)
- Date of publication
- Sep 2021
- Publisher
- SAE International
- Language
- English
- Event
- SAE Powertrains, Fuels & Lubricants Digital Summit
Detailed Information
| Author(E) | 1) Lorenzo Sforza, 2) Tommaso Lucchini, 3) Gianluca Montenegro, 4) Cagdas Aksu, 5) Taisuke Shiraishi |
|---|---|
| Affiliation(E) | 1) Politecnico di Milano, 2) Politecnico di Milano, 3) Politecnico di Milano, 4) Nissan Motor Co Ltd, 5) Nissan Motor Co Ltd |
| Abstract(E) | Cycle-To-Cycle Variability (CCV) must be properly considered when modeling the ignition process in SI engines operating with ultra-lean mixtures. In this work, a strategy to model the impact of the ignition type on the CCV was developed using the RANS approach for turbulence modelling, performing multi-cycle simulations for the power-cycle only. The spark-discharge was modelled through a set of Lagrangian particles, introduced along the sparkgap and interacting with the surrounding Eulerian gas flow. Then, at each discharge event, the velocity of each particle was modified with a zero-divergence perturbation of the velocity field with respect to average conditions. Finally, the particles velocity was evolved according to the Simplified Langevin Model (SLM), which keeps memory of the initial perturbation and applies a Wiener process to simulate the stochastic interaction of each channel particle with the surrounding gas flow. The particles diameter was also evolved, according to both the energy transfer from the electrodes and the local stretched laminar flame speed. The proposed methodology was assessed against experimental measurements from a pent-roof high-tumble single-cylinder SI engine, equipped with an electrical circuit able to provide both standard and enhanced discharge events. Promising results were achieved in terms of predicted IMEP and its CoV. |
