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An FCS-MPC-based open-circuit and current sensor fault diagnosis method for traction inverters with two current sensors.
- Source :
-
International Journal of Electrical Power & Energy Systems . Jan2023, Vol. 144, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- Effective fault diagnosis methods can improve the reliability of the two-level inverter used in traction systems. Both the open-circuit (OC) fault and current sensor fault can affect the phase currents of the inverter, which makes it difficult to distinguish them. In this paper, a diagnosis method for OC faults and current sensor faults is proposed, which is based on finite control set-model predictive control (FCS-MPC). First, the cost function is constructed and the inverter is controlled by the FCS-MPC. Then, the actual and estimated values of the cost function are calculated. The difference between them is applied to fault detection. Next, Combine the command signals and current direction, the number of affected sampling points in a period is counted and normalized. Different faults correspond to different percentages and this feature is used to determine fault location. Finally, the hardware-in-the-loop (HIL) platform is built, the feasibility and effectiveness of the proposed fault diagnosis method are verified by the HIL tests. • The finite control set-model predictive control is a promising control strategy for traction inverter. • The residual of cost function is introduced can provides a new idea for fault diagnosis. • The interference between current sensor and transistor faults should be considered to avoid false alarms. • The fault diagnosis method that requires only two current sensors is more suitable for practical applications. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01420615
- Volume :
- 144
- Database :
- Academic Search Index
- Journal :
- International Journal of Electrical Power & Energy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 159215649
- Full Text :
- https://doi.org/10.1016/j.ijepes.2022.108526