Abstract
Knocking in SI (Spark Ignition) engines is one of the most addressable problems. If not detected in early stages, it causes a severe damage to an SI engine. Various techniques have been proposed so far, in order to detect early knock symptoms. This paper presents a novel approach to detect knocking using technique of Artificial Intelligence. A four stroke, single cylinder engine is simulated using GT Power engine simulation software. Data is generated through simulation for both knock and no-knock conditions. A CMAC (Cerebellar Model Articulation Controller) based neural network is then applied as an AI (Artificial Intelligence) tool to distinguish between knock and no-knock conditions. The results show a promising future for CMAC neural networks as a technique to detect knocking in SI engines.
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