Online Monitoring of Interturn Short Circuit Current in PMSMs

conference paper

English

This paper extends the previously published parameter estimation-based approach to interturn short circuit diagnostics in permanent magnet synchronous motors by real-time monitoring of hidden machine states after fault occurrence. The designed monitoring method relies on an adaptive formulation of the Kalman filter, which assumes interdependence between measurement and process noise variables. A variable forgetting factor not only mitigates the impact of the process model uncertainty but also facilitates the simultaneous operation of the monitoring algorithm and fault indicator estimation. Furthermore, contributions of fault current and healthy machine model to stationary reference frame currents are estimated from an advanced discrete-time motor description reflecting a stator winding arrangement inside a motor's case. The monitoring algorithm is validated in steady state, torque load transient, and velocity transient laboratory experiments with diverse fault severity values.

discrete-time systems, fault currents, fault diagnosis, Kalman filters, permanent magnet machines, short-circuit currents, state estimation

ZEZULA, L.; BLAHA, P.

10. 3. 2025

IEEE

978-1-6654-6454-3

IECON 2024: 50th Annual Conference of the IEEE Industrial Electronics Society

6

https://ieeexplore.ieee.org/document/10905190

http://hdl.handle.net/11012/250727

main.pdf