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To achieve high power output and good efficiency and to comply with increasingly stricter emission standards, modern combustion engines require a more complex engine design, which results in a higher number of control parameters. As the measurement effort and the number of sensors for engine development at the test bed continue to increase, it is becoming nearly impossible for the test bed engineer to manually check measurement data quality. As a result, automated methods for analysis and plausibility checks of measurement data are necessary in order to find faults as soon as they occur and to obtain test results of the highest possible quality. This paper presents a methodology for automated fault diagnosis on engine test beds. The methodology allows reliable detection of measurement faults as well as the identification of the root cause of faults.

Experimental investigations on engine test beds represent a significant cost in engine development. To reduce development time and related costs, it is necessary to check the quality of measurements automatically whenever possible directly on the test bed to allow early detection of faults. A fault diagnosis system should provide information about the presence, cause and magnitude of an inconsistency in measurement. The main challenge in developing such a system is to detect the fault quickly and reliably. However, only faults that have actually occurred should be detected because the user will only adopt a system that provides accurate results. This paper presents a methodology for automated fault diagnosis at engine test beds, starting with an explanation of the general procedure. Next, the methods applied for fault detection are introduced.