Innovations in Axial Flux Permanent Magnet Motor Thermal Management for High Power Density Applications
Bibliographic record
Abstract
For aerospace applications, power density is a major driving force in the design of electrified powertrains. At the forefront is the challenging design of electric motors with high efficiencies, torque, and power capabilities. Due to its high performance, the Axial Flux Permanent Magnet (AFPM) Motor is expected to be one of the leading technologies to meet the demands of these industries. Finding the balance between the cooling system’s effectiveness and subsequent parasitic losses is key to utilizing these performance benefits. Single stator double rotor topologies achieve the best torque density and lower stator losses, however are more challenging to cool as the stator is in the center of the motor. Single stator single rotor and double stator machines are less challenging to cool but typically have lower power density. Rotor air cooling is discussed including the effectiveness of blades, meshes, and vents which can be optimized to prevent demagnetization. Stator cooling is critical as many machines maximize current density producing a large amount of heat. The chosen strategy depends on the machine topology and can be accomplished by several strategies, including jackets, fins, channels, immersion cooling, hollow coils, and heat pipes.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".