Design of a Switched Reluctance Motor for a 48 V Hybrid Electric Vehicle Propulsion Application
Bibliographic record
Abstract
Switched Reluctance Motors (SRMs) are a promising motor type to reduce the cost of electrified vehicle propulsion systems in the near future. This study presents the design and analysis of a 12/8 SRM for a 48 V, 30 kW Full Hybrid Electric Ve-hicle (FHEV) propulsion application. The proposed design aims to meet the performance requirements of the target Permanent Magnet Synchronous Motor (PMSM) with an SRM that does not require rare-earth permanent magnets. This work addresses the design challenges of the SRM of this application, especially in high-speed operating region. The performance of the SRM drive has been optimized for the entire torque-speed curve using a weighted single objective genetic algorithm based optimization in MATLAB/Simulink. The efficacy of the SRM design is validated through simulation studies for various operating points of the targeted application.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".