Model-Based Fault Detection Using Parameter Estimation in Automotive EPGS Systems

This paper presents a unique method for self- fault detection and diagnosis in automotive electric power generation system. The presented model-based approach using parameter estimation allows detecting the change in the dynamic behavior of the main variables in correlation to the presence of fault. The approach employs the available measurements in the vehicle to detect the mechanical faults and enables self-diagnostic and communication on a higher level. The results of this approach are compared with the ones provided of the conventional signal-based methods to show the discrepancies and provide a proof of concept for further analysis.