Investigation of 6-phase surface PM machines with concentrated windings for reduction in space harmonics, leakage inductance and magnet loss in direct-drive EV
Bibliographic record
Abstract
Surface Permanent Magnet (SPM) synchronous machines with fractional slot concentrated windings (FSCW) have been found to provide high torque density with low torque ripple and cogging torque, making them suitable for direct-drive electric vehicle (EV) application. This paper initially analyses a 3-phase 36/30 FSCW SPM machine for direct-drive application in terms of its space harmonics, steady-state characteristics and losses over a wide speed range using winding function theory and MTPA control in conjunction with finite element analysis (FEA). It was found that the 3-phase machine produces high space harmonics in the flux density which resulted in increased magnet eddy current loss and high stator leakage inductance which leads to extended constant power speed range (CPSR) as well. Since, the CPSR requirement for a direct-drive EV motor is lesser than that of a high-speed EV motor, there is scope for reducing the stator leakage inductance. Hence, a 6-phase 36/30 FSCW SPM machine employing the same stator, rotor and current rating as that of the 3-phase machine is investigated in an effort to reduce space harmonics, stator leakage inductance and magnet eddy current losses while delivering the desired output characteristics. Also, an analytical method to calculate the 6-phase machine d- and q-axis inductances from winding and slot permeance functions are proposed. Thereafter, a comparative performance analysis is conducted on both the 3-phase and 6-phase machines designed and results are discussed.
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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".