Browse Publications Technical Papers 2019-01-0260
2019-04-02

Experimental and Numerical Analysis of Pre-Chamber Combustion Systems for Lean Burn Gas Engines 2019-01-0260

The current trend in automobiles is towards electrical vehicles, but for the most part these vehicles still require an internal combustion engine to provide additional range and flexibility. These engines are under stringent emissions regulations, in particular, for the reduction of CO2. Gas engines which run lean burn combustion systems provide a viable route to these emission reductions, however designing these engines to provide sustainable and controlled combustion under lean conditions at λ=2.0 is challenging. To address this challenge, it is possible to use a scavenged Pre-Chamber Ignition (PCI) system which can deliver favorable conditions for ignition close to the spark plug. The lean charge in the main combustion chamber is then ignited by flame jets emanating from the pre-chamber nozzles. Accurate prediction of flame kernel development and propagation is essential for the analysis of PCI systems. A modelling approach is proposed based on the Dynamic Discrete Particle Ignition Kernel model coupled with the G-equation combustion model. The model is validated for an air/methane academic benchmark. The approach is then applied to the investigation of performance of three pre-chamber designs developed within Horizon 2020 GASON project in conjunction with the experimental investigation of these pre-chambers mounted on Rapid Compression Expansion Machine (RCEM). The investigated pre-chamber designs vary with respect to the tangential nozzle angle and volume. The study focusses on a lean limit of the proposed system’s operation with the main charge at λ=2.0 and a variation of pre-chamber design and scavenging level. The comparison of the simulation results with the experimental observations demonstrates good accuracy of the developed model. In addition, the combined experimental and modelling provides insights into the effect of pre-chamber geometry on potential performance.

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