As electrical and electronic systems (EES) steadfastly increase their functional complexity and connectedness, they pose ever-growing challenges in fault analysis prevention. Many EES faults are intermittent, emerging (new faults), or cascading, and cannot be addressed by the traditional component-level diagnostic design. Leveraging the latest advancements in Network Science, we take the holistic approach to model and analyze the highly interrelated in-vehicle EES as layered sub-networks of hardware components, software components, and communication links.

This paper addresses the problem of system design for diagnosability. Specifically, it focuses on design of built-in self-tests (BISTs) for subsystems based on electronic control units (ECUs). The BISTs play a major role in diagnosis of the systems and in particular in determining if the failure is in the ECU or externally in the sensors, detectors, or actuators. The design of BISTs involves a tradeoff between the diagnostic benefit gained by the presence of a BIST versus cost of providing it in the system.

This paper addresses the problem of system design for diagnosability. Specifically, it focuses on design of built-in self-tests (BISTs) for subsystems based on electronic control units ECUs). The BISTs play a major role in diagnosis of the systems and in particular in determining if the failure is in the ECU or externally in the sensors, detectors, or actuators. The design of BISTs involves a tradeoff between the diagnostic benefit gained by the presence of a BIST versus cost of providing it in the system.