Abstract
To enhance the reliability of in-wheel motors, it is crucial to avoid failures in the motors, sensors and the motor drives. However, in-wheel motor structures formed on
permanent magnet synchronous motors (PMSMs) and voltage source inverter (VSI) using pulse-width modulation (PWM) are fragile to power-converter component faults such as power switches. Furthermore, switching device faults accrue in the form of open circuits or short circuits. An open circuit fault imposes phase voltage imbalances to each phase voltage. This paper presents a new approach to detecting the imbalanced phase voltage due to the open-circuit fault in the inverters employing
a super-twisting algorithm-based sliding mode observer. The combination of the proposed observer with the Extended Kalman filter (EKF) results in a robust observer which can be used under the noisy measurement conditions that are unavoidable
in industrial applications. In addition, the simulated observer applies a model-based fault detection algorithm, enabling the fault to be isolated more easily and reliably than when using signal processing methods.
permanent magnet synchronous motors (PMSMs) and voltage source inverter (VSI) using pulse-width modulation (PWM) are fragile to power-converter component faults such as power switches. Furthermore, switching device faults accrue in the form of open circuits or short circuits. An open circuit fault imposes phase voltage imbalances to each phase voltage. This paper presents a new approach to detecting the imbalanced phase voltage due to the open-circuit fault in the inverters employing
a super-twisting algorithm-based sliding mode observer. The combination of the proposed observer with the Extended Kalman filter (EKF) results in a robust observer which can be used under the noisy measurement conditions that are unavoidable
in industrial applications. In addition, the simulated observer applies a model-based fault detection algorithm, enabling the fault to be isolated more easily and reliably than when using signal processing methods.
| Originalsprache | englisch |
|---|---|
| Titel | 2023 ICM – IEEE International Conference on Mechatronics |
| Publikationsstatus | Veröffentlicht - 2023 |
| Veranstaltung | IEEE International Conference on Mechatronics: IEEE ICM 2023 - Loughborough University, Loughborough, Großbritannien / Vereinigtes Königreich Dauer: 15 März 2023 → 17 März 2023 https://iten.ieee-ies.org/events/2022/2023-icm-ieee-international-conference-on-mechatronics/ |
Konferenz
| Konferenz | IEEE International Conference on Mechatronics |
|---|---|
| Kurztitel | IEEE ICM 2023 |
| Land/Gebiet | Großbritannien / Vereinigtes Königreich |
| Ort | Loughborough |
| Zeitraum | 15/03/23 → 17/03/23 |
| Internetadresse |