Knock Limited Spark Advance Prediction of a Direct-Injection Spark-Ignition Engine Using a Livengood-Wu Integral Transport Equation Based Knock Model

2022-01-7054

10/28/2022

Features
Event
SAE 2022 Vehicle Electrification and Powertrain Diversification Technology Forum
Authors Abstract
Content
Knocking combustion limits the application of high compression ratios in gasoline engines and therefore obstructs the improvement of thermal efficiency. Predicting knock and knock limited spark advance (KLSA) can guide engine upfront design and optimization before the prototype is built. This study employed three-dimensional computational fluid dynamics (CFD) simulations coupled with an accurate and computation-efficient knock model to predict the KLSA of a turbocharged direct-injection spark-ignition engine. The knock model predicted the end-gas auto-ignition based on a Livengood-Wu (L-W) integral transport equation instead of directly using detailed chemical mechanisms, which was able to achieve a fast computation time. To keep the predictability, ignition delay data was calculated using zero-dimensional chemistry simulation and tabulated a priori, which was then used for CFD simulation on the fly. The results showed that the CFD model was able to well reproduce engine combustion processes and predict KLSA under different operating conditions. It showed that the errors between predicted and measured KLSA were within 2° crank angles. In addition, the model successfully predicted the increasing knocking tendency when the intake temperature increased, which further verified the accuracy of the knock model.
Meta TagsDetails
DOI
https://doi.org/10.4271/2022-01-7054
Pages
10
Citation
Wu, Z., Han, Z., Meng, S., Li, T. et al., "Knock Limited Spark Advance Prediction of a Direct-Injection Spark-Ignition Engine Using a Livengood-Wu Integral Transport Equation Based Knock Model," SAE Technical Paper 2022-01-7054, 2022, https://doi.org/10.4271/2022-01-7054.
Additional Details
Publisher
Published
Oct 28, 2022
Product Code
2022-01-7054
Content Type
Technical Paper
Language
English