Model-Free Predictive Control for PMSM Incorporating Flux-weakening
Bibliographic record
Abstract
In recent years, permanent magnet synchronous motors (PMSMs) have gained significant attention across various industrial sectors, particularly in transportation, owing to their distinct advantages over alternative motor technologies. Notably, PMSMs exhibit higher power density and possess the potential for wide flux weakening operation, thereby extending the speed range of operation—a critical attribute in electric vehicle applications. However, the sensitivity of PMSM control approaches to variations in machine parameters presents a notable challenge, as it can lead to degradation in controller performance when discrepancies arise between modeled parameters and real-world conditions. Addressing this concern, this study introduces a model-free adaptation of finite control set (FCS) predictive control (FCS-MFPC) tailored for flux weakening (FW) operation. Through simulation analysis conducted over the US Environmental Protection Agency Urban Dynamometer Driving Schedule, the performance of this controller is examined. Additionally, the performance of the controller is compared to conventional FCS-MPC. To facilitate a comprehensive comparison, criteria such as reference tracking error and drive efficiency are considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".