Fault Detection in Automotive Network Embedded Electronics Systems

Focusing on the challenges posed by advanced automotive electronics, this research analyzes data from the Controller Area Network of two vehicles. It evaluates various data mining and feature extraction techniques to develop fault detection methods applicable to complex systems. Utilizing data from both a standard vehicle and an experimental test bed, the study documents the effectiveness of mathematical methods originally used in statistics and digital signal processing. The culmination involves creating a model of the network bus to identify faults effectively.