Session: 06-06 Abnormal Combustion Modeling

Paper Number: 197472

197472 - Cell-Based Livengood Wu Ignition Integral Model to Predict Knock in Spark-Ignited Engines 

Abstract: 

Engine knock continues to be a significant barrier to further enhancing the efficiency of spark-ignited engines. Improving the efficiency often requires careful balancing of critical parameters such as compression ratio and spark advance.  However, knock occurrence severely restricts the design possibilities. To improve knock limits of an engine, it is essential to understand and develop effective means to control the following two key design aspects: (1) the maximum spark advance possible before the onset of knock, also referred to as the knock limited spark advance (KLSA);  and (2) the locations inside the cylinder that are most susceptible to knocking. To that end, a RANS-based knock model is developed and presented in this study. Built upon the multi-zone, well-stirred reactor combustion model in Converge, Livingood-Wu (L-W) ignition integral for each cell ahead of the flame front is estimated via an ignition delay look-up model that consists of tabulated ignition delay values calculated utilizing tailored chemical kinetic mechanisms with respect to cell-averaged pressure, unburned temperature, equivalence ratio and EGR dilution. The unburned temperature is calculated by solving a transport equation for the unburned species and unburned enthalpy, while the flame front is tracked via a progress variable. Moreover, the sub-grid turbulent variations in the unburnt temperature and equivalence ratio are captured by introducing a multivariate cell-based Gaussian PDF model. Implementing this cell-based L-W ignition integral approach, knock prediction results are presented for a tumble-based, spark-ignited EGR natural gas engine, thereby highlighting the capability of the ensemble-averaged RANS framework to effectively predict knock-limited operation for real-world applications.

Presenting Author: Arun Ravindran Cummins Inc.

Presenting Author Biography: - 2021 PhD graduate from ERC, UW Madison. Advisor - Prof. Sage Kokjohn
- Masters in Mechanical Engineering specialized in Combustion Modeling from IIT Madras
- Joined Cummins in 2021
- Research at Cummins focusses on 3D combustion modeling of Tumble/Swirl SI engines.

Authors:

Arun Ravindran Cummins Inc.
Zhang Yu Cummins Inc
Cao Li Cummins Inc.