Knock Intensity Distribution and a Stochastic Control Framework for Knock Control
Mateos Kassa, Carrie Hall, Michael Pamminger, Thomas Wallner

TL;DR
This paper characterizes engine knock intensity using a mixed lognormal distribution and proposes a stochastic control framework that adjusts spark timing based on knock likelihood, aiming to improve engine efficiency.
Contribution
It introduces a probabilistic model for knock intensity using mixed lognormal distribution and develops a stochastic control approach for better knock management.
Findings
Knock intensity follows a mixed lognormal distribution with over 95% fitting accuracy.
The proposed stochastic control adjusts spark timing based on knock probability.
Improved knock control can enhance engine performance and fuel efficiency.
Abstract
One of the main factors limiting the efficiency of spark-ignited engines is the occurrence of engine knock. In high temperature and high pressure in-cylinder conditions, the fuel-air mixture auto-ignites creating pressure shock waves in the cylinder. Knock can significantly damage the engine and hinder its performance; as such, conservative knock control strategies are generally implemented that avoid such operating conditions at the cost of lower thermal efficiencies. Significant improvements in the performance of conventional knock controllers are possible if the properties of the knock process are better characterized and exploited in knock controller designs. One of the methods undertaken to better characterize knocking instances is to employ a probabilistic approach, in which the likelihood of knock is derived from the statistical distribution of knock intensity. In this paper, it…
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