Advanced 1-D Ignition and Flame Growth Modeling for Ignition and Misfire Predictions in Spark Ignition Engines Southwest Research Institute

Format:

Book

Conference/Event

Author/Creator:

Moiz, Ahmed Abdul, author.

Contributor:

Zainal Abidin

Briggs, Thomas

Conway, Graham

Conference Name:

SAE WCX Digital Summit (2021-04-13 : Live Online, Pennsylvania, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2021

Summary:

Simulating high amounts of exhaust gas recirculation in spark ignited engines to predict combustion using the currently available CFD modeling approaches is a challenge and does not always give reasonable matches with experimental observations. One of the reasons for the mismatch lies with the secondary circuit treatment of the ignition coil and the resulting energy deposition or a complete lack of it thereof. An ignition modeling approach is developed in this work which predicts the energy transfer from the electrical circuit to the gases in the combustion chamber leading to flame kernel growth under high EGR and high gas flow velocity conditions. Secondary circuit sub-model includes secondary side of the coil, spark plug and spark gap. The sub-model calculates the delivered energy to the gas based on given circuit properties and total initial electrical energy. The delivered energy is sent to the 1-D sub-model where heat conduction, mass and energy balance are solved to get instantaneous flame kernel size. Turbulence and heat loss to the electrodes are considered in the model. The model has been calibrated with calorimeter test data to match delivered energy and spark duration. Modeling the secondary circuit enables the code to predict the energy received by the gas as a function of secondary circuit properties and gas flow in the gap. The developed model is designed to simulate an advanced ignition system, works not only under low EGR and modest flow conditions but also under high EGR and high flow conditions and is able to predict misfire cases

Notes:

Vendor supplied data

Publisher Number:

2021-01-0376

Access Restriction:

Restricted for use by site license