Enhancing Open-End Winding Induction Motor Performance for Fault-Tolerant All-Wheel Drive EVs With ANN-Based DTC
This paper presents an advanced control strategy for all-wheel drive (AWD) electric vehicles (EVs) based on artificial neural network (ANN)-enhanced direct torque control (DTC) for open-end winding induction motors (OEWIMs). The proposed ANN dynamically adapts to various inverter faults by optimally utilizing asymmetric voltage vectors, eliminating the need for fault-specific control mechanisms. The proposed control was validated under the FTP 75 drive cycle, demonstrating stable vehicle operation and delivers maximum available torque during faults by adjusting the flux trajectory. The experimental results demonstrate stable and improved EV operation under normal and fault conditions throughout the drive cycles.
Authors
- Kaif Ahmed Lodi (ORCID: https://orcid.org/0000-0002-9851-3167)
- Khaled Al Jaafari (ORCID: https://orcid.org/0000-0003-1990-5486)
- Abdul R. Beig (ORCID: https://orcid.org/0000-0002-1519-7454)
Institutions
- Khalifa University of Science and Technology (AE)
Publication Details
- Journal
- IEEE Transactions on Transportation Electrification
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1109/tte.2025.3566711
- Citations
- 7
- Primary Topic
- Sensorless Control of Electric Motors
- Type
- article
- Field-Weighted Citation Impact
- 5.11