Design of a permanent magnet synchronous machine for a flywheel energy storage system within a hybrid electric vehicle
Bibliographic record
Abstract
As an energy storage device, the flywheel has significant advantages over conventional chemical batteries, such like higher energy density, higher efficiency, longer life time, and less environment pollution. Flywheel technology have been widely used in varies of areas, including power system, space craft, and hybrid electric vehicles (HEV). An effective flywheel system mainly attribute to its good motor /generator (M/G) design. This paper describes the design of a permanent magnet synchronous machine (PMSM) as an M/G suitable for integration in a flywheel energy storage system within a large HEV. The operating requirements of the application include wide power and speed ranges combined with high total system efficiency. The machine described in this paper has been designed to meet these requirements together with a number of additional constrains that include restricted dimensions, voltage and current limits. Along with presenting the design, essential issues upon PMSM design including cogging torque, iron losses and total harmonic distortion (THD) are investigated, and certain strategies as solutions to those issues have been introduced and compared. An iterative approach combining lumped parameter analysis with 2D finite element analysis (FEA) is used, and the final design is also presented showing great performances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".