Real-Time Prediction of Pre-ignition and Super-Knock in Internal Combustion Engines

Super-knock is a phenomenon triggered by pre-ignition and has limited the design envelope of internal combustion engines (ICEs) in terms of power density. This poses a huge challenge for the automotive industry where engine sizes have been continuously decreasing due to the demand for weight savings and integration with electrified powertrains. Such downsized engines typically require increased boost pressure, availing conditions conducive to pre-ignition, which in turn may trigger super-knock. Traditionally, this and other forms of knock have been managed by way of a “detection and mitigation” approach in place of “perdition and avoidance” due to an evolving understanding of corresponding combustion dynamics, as well as the incapability of emerging real-time computational methods to perform and actuate over the timescale required. In this study, a data-driven algorithm is used to extract (and adapt) a globally linearized system representation using eigen-time-series, isolating the dynamic modes of the system to capture underlying effects leading to pre-ignition without the need for physics-based modeling. This approach is a unique application of the “Hankel Alternative View of Koopman” (HAVOK) analysis for chaotic systems and can be executed on board an engine control module supplying a buffer of recent to latest time-step data to predict an impending pre-ignition event. The proposed design does not require any change to existing sensors and actuators in the existing knock management system architecture, nor would it require any significant increase in computational capacity in terms of the associated engine control unit. A simulation was conducted with real super-knock data to nominally test the applicability of the algorithm. From this training dataset, the linearized dynamic system was able to predict pre-ignition approximately 2.27 s prior to the event, which is adequate to take mitigating action. Further validation runs covering low, medium, and high engine speeds within the envelope of low-speed pre-ignition (LSPI) generated similar results.