Decoupled Design of Fault-Tolerant Control for Dual-Three-Phase IPMSM With Improved Memory Efficiency and Reduced Current RMS
Bibliographic record
Abstract
Fault tolerance is critical to real-time control of the dual-three-phase interior permanent magnet synchronous machine (IPMSM). This article proposes an efficient decoupled design for fault-tolerant control (FTC) of dual-three-phase IPMSMs to improve the average torque and minimize the current root mean square (rms) for torque ripple and loss reduction under the open-phase fault. Specifically, the FTC design is divided into two subtasks to derive the FTC strategy with a simplified design, in which the two subtasks are the fundamental current design and the harmonic current design. The optimal current solution to FTC is derived in a memory- and computation-efficient way. The proposed solution can achieve better transient performance and reduce the current rms for FTC, which is critical to practical applications with dynamic changing loads. In comparison with existing methods, the proposed FTC can effectively reduce the request of memory and computation resources from the drive system. Extensive experiments and comparisons are conducted to evaluate the proposed FTC on a laboratory dual-three-phase IPMSM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".