Robust Fault Diagnosis of Sensor Faults in Power Converter used in Hybrid Electric Vehicle

Abstract

With the intensive use of power converters in modern hybrid vehicles, the implementation of effective fault diagnosis schemes becomes essential to ensure the reliability, safety and robustness of the electrical powertrain. Faults in such systems can occur anywhere and at any time leading to extremely serious consequences. This paper addresses the detection and isolation of sensor faults in a bidirectional DC/DC power converter system interfacing the main energy storage unit and the AC drive in a hybrid electric vehicle. A residual-based fault diagnosis scheme that timely detects and localizes sensor faults in the examined system is designed. The proposed method enhances the scheme previously presents in (Al-Sheikh, 2015) by utilizing a bank of piece wise switched Kalman filters along with an optimal disturbances decoupling observer suitable for switching systems. The performance of the fault diagnosis scheme is enhanced by including sources of disturbances and uncertainties to the piece wise switched state-space model of the converter. These uncertainties present variations in the parameters of the converter; a problem common in power converter systems.