Knock feedback control strategies: A review

Knocking combustion is a limiting factor in otherwise highly efficient modern downsized engines, which therefore require some form of knock control strategy. These strategies are distinctive because knock behaves as a cyclically independent random process. An increased focus on the stochastic aspect of this problem has opened up new possibilities for controller design, as seen in the recent literature. This paper aims to organize and present some of the principal ideas and approaches in a consistent and structured framework. Controllers are broadly classified by the signal / statistic used for feedback and the method of its estimation. Both classical and advanced knock ‘event-based’ strategies apply a threshold to the measured knock intensity value and then regulate the resulting knock event probability. Knock ‘intensity-based’ controllers, by contrast, use the more informative raw knock intensity signal for feedback, and generally assume these intensities conform to a log-normal distribution. More recently, Bayesian estimators have been used in both event-based and intensity-based control, as an alternative to frequentist estimation methods. Within each of these broad classes, individual control strategies are discussed in detail, and, in some cases, simplifying expressions are derived. More generally, the choice of control objective, estimation method, and error metric are also discussed in depth since these have a significant impact on closed loop performance.