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Distributed Fault Diagnosis for Networked Embedded Systems

In a system like a Scania heavy duty truck, faultcodes (DTCs) are generated and stored locally in the ECUs when components, e.g. sensors or actuators,malfunction. Tests are run periodically to detect failure in the system. The test results are processed by the diagnostic system that tries to isolate the faulty components and set local faultcodes.

Currently, in a Scania truck, local diagnoses are only based on local diagnostic information, which the DTCs are based upon. The diagnosis statement can, however, be more complete if diagnoses from other ECUs are considered. Thus a system that extends the local diagnoses by exchanging diagnostic information between the ECUs is desired. The diagnostic information to share and how it should be done is elaborated in this thesis. Further, a model of distributed diagnosis is given and a few distributed diagnostic algorithms for transmitting and receiving diagnostic information are presented.

A basic idea that has influenced the project is to make the diagnostic system scalable with respect to hardware and thereby making it easy to add and remove ECUs. When implementing a distributed diagnostic system in networked real-time embedded systems, technical problems arise such as memory handling, process synchronization and transmission of diagnostic data and these will be discussed in detail. Implementation of a distributed diagnostic system is further complicated due to the fact that the isolation process is a non deterministic job and requires a non deterministic amount of memory.

Dan Hallgren and Håkan Skog


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Last updated: 2021-11-10