Modulation Depth Maximization for High Phase Count Drives With Emphasis on Variable Pole Operation
High-phase-count machines are well known to have reduced dc bus utilization compared to conventional three-phase drives. High-phase-count machines for fault tolerance and variable-pole induction machine drives are two examples. Variable-pole machines need more than three phases to support electronic pole changing. This article proposes two complementary approaches to improve variable pole induction machine base speed and high-speed torque capability. Base speed improvement is achieved with a modulation technique that increases dc bus utilization by 11.5% for the highest operating pole count. An optimization framework for loss minimization is developed considering the simultaneous operation of multiple poles and cases, including no synchronization between operating poles, stator flux synchronization, and stator voltage synchronization. The framework shows that voltage synchronization improves torque by 49.5% at maximum operating speed. A proposed control architecture enables one pole configuration to operate under vector control and others under scalar control, thereby eliminating parameter dependence for stator voltage synchronization. Experimental results on a toroidally wound 36-slot machine validate the proposed modulation strategy, control architecture, and high-speed torque improvement from synchronized stator voltage injection.
Authors
- Anuj Maheshwari (ORCID: https://orcid.org/0000-0003-3001-5839)
- Debranjan Mukherjee (ORCID: https://orcid.org/0000-0002-6326-4981)
- Philip T. Krein (ORCID: https://orcid.org/0000-0001-8048-6968)
- Elie Libbos (ORCID: https://orcid.org/0000-0003-3008-4914)
- Arijit Banerjee (ORCID: https://orcid.org/0000-0001-9568-2371)
- Dipanjan Mazumdar (ORCID: https://orcid.org/0000-0002-4019-8969)
- Soumil Chaubal
- P. Bajaj (ORCID: https://orcid.org/0009-0000-0042-8048)
Institutions
- Indian Institute of Technology Kharagpur (IN)
- University of Illinois Urbana-Champaign (US)
- Texas Instruments (United States) (US)
Publication Details
- Journal
- IEEE Transactions on Industry Applications
- Published
- 2025-05-19
- DOI
- https://doi.org/10.1109/tia.2025.3571361
- Primary Topic
- Iterative Learning Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00