Model-based fault diagnosis applied to an SI-Engine

A diagnosis procedure is an algorithm to detect and locate (isolate) faulty components in a dynamic process. In 1994 the California Air Resource Board released a regulation, called OBD II, demanding a thorough diagnosis system on board automotive vehicles. These legislative demands indicate that diagnosis will become increasingly important for automotive engines in the next few years. To achieve diagnosis, redundancy has to be included in the system. This redundancy can be either hardware redundancy or analytical redundancy. Hardware redundancy, e.g. an extra sensor or extra actuator, can be space consuming or expensive. Methods based on analytical redundancy need no extra hardware, the redundancy here is generated from a process model instead. In this thesis, approaches utilizing analytical redundancy is examined. A literature study is made, surveying a number of approaches to the diagnosis problem. Three approaches, based on both linear and non-linear models, are selected and further analyzed and complete design examples are performed. A mathematical model of an SI-engine is derived to enable simulations of the designed methods