DISTRIBUTED DIAGNOSIS FOR EMBEDDED SYSTEMS IN AUTOMOTIVE VEHICLES

摘要

Fault diagnosis is important for automotive vehicles, due to economic reasons such as efficient repair and fault prevention, and legislations which mainly deals with safety and pollution. In embedded systems with dozens of electronic control units that states local diagnoses, it can be arbitrary difficult to find which combination of local diagnoses that points at the correct faulty components. An algorithm is presented that both finds the diagnoses that in themselves are complete and chooses only those diagnoses that are more likely to be correct, this restriction is wanted due to the limitations in processing power, memory, and network capacity. The embedded system in a Scania heavy duty vehicle has been used as a case study to find realistic requirements on the algorithm.