High-resolution low-cost rotor position sensor for traction applications
Bibliographic record
Abstract
The paper presents for the first time the use of a low cost Hall effect position sensor for a synchronous reluctance machine (SynRM). The use of vector control for a SynRM requires information of the rotor position. Already the SynRM is independent of the use of permanent magnets (PMs) which results in reduced cost of the SynRM. Hence the use of a low cost position sensor contributes to an additional cost reduction of the electric drive for traction applications. The paper also presents a comparison between the low cost position sensor with the digital hall effect position sensor used in the electric power steering (EPS) machines. The different dynamics of the SynRM were demonstrated through the use of the low cost position sensor. The low cost position sensor had a relatively simpler algorithm for position information and better position resolution. Through the use of the low cost position sensor the machine produced low torque ripples of less than 9% with a total current harmonic distortion (THD) of less than 2%. The proposed position sensor registered an error less than 1 mechanical degree when compared with a 12-bit industrial encoder.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".