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Record W2238832878

ADVANCED THERMAL MANAGEMENT FOR A SWITCHED RELUCTANCE MACHINE

2016· dissertation· en· W2238832878 on OpenAlexfundno aff
Richard Marlow

Bibliographic record

VenueMacSphere (McMaster University) · 2016
Typedissertation
Languageen
FieldEngineering
TopicRadiative Heat Transfer Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanada Excellence Research Chairs, Government of Canada
KeywordsSwitched reluctance motorThermal management of electronic devices and systemsEngineeringAutomotive engineeringMechanical engineeringComputer scienceRotor (electric)
DOInot available

Abstract

fetched live from OpenAlex

The thermal management of electric machines is investigated with the application of techniques to a Switched Reluctance Machine and a high-speed Switched Reluctance Machine. Two novel concepts for said management of a Switched Reluctance Machine are proposed and developed: Inter-Laminate Cooling and a Continuous Toroidal Winding.
\n\tThe Inter-Laminate Cooling concept is developed with application to an iron core inductor which serves as a proxy for the electric machine. The experimental results confirmed the capability of the method, expressed by the effectiveness, which defines the performance measure of the applied cooling method; a concept which itself is equally applicable to other cooling methods that may be applied to any electric machine. The effectiveness also describes the gain in allowable input power to the machine which is realized to reach the same thermal limit versus the case without Inter-Laminate Cooling. The Inter-Laminate Cooling was not applied in experimental test to a Switched Reluctance Machine due to the present economic and fabrication limitations.
\n\tThe Continuous Toroidal Winding concept, originally conceived to permit the consideration of a fluid capillary core type of winding to enhance machine cooling, is developed to allow for peripheral cooling of the machine windings and end windings. The Continuous Toroidal Winding version of the Switched Reluctance Machine is investigated for both its thermal and electrical performance in the context of a machine that is equivalent electromagnetically to its conventional counterpart. The Continuous Toroidal Winding Switched Reluctance Machine was found to perform thermally as tested, in a manner superior to that of the conventional machine where the Toroidal machine was simulated and researched at an equivalent level of operation to the conventional machine. The electrical performance of the Toroidal Switched Reluctance Machine although supportive of the simulation analysis used to develop the machine, was not fully conclusive. This may have been due to problematic iron cores used in the construction of the experimental machines. 
\n\tThe application of the Inter-Laminate Cooling method to a Switched Reluctance Machine is considered on an analytical basis for the special case of a High Speed Switched Reluctance Machine and found to be of net positive benefit as the machine’s iron losses are dominant over its copper losses. Application of the Inter-Laminate Cooling method to a lower speed machine, whilst beneficial, is not sufficient to significantly impact the temperature of the machine’s windings such that it would offset the loss of specific torque and power. As such, Inter-Laminate Cooling is only applicable where the net benefit is positive overall; in that the gain in input power realized is sufficient to overcome the loss of specific power and torque which will occur due to the increased machine volume.
\n\tThe “effectiveness” and “gain” approach for the evaluation of cooling methods applied to electric machines is a concept which should be adopted to aid in the comparative understanding of the performance of myriad different cooling methods being applied to electric machines both in research and practice, of which there is only minimal understanding.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.008
GPT teacher head0.197
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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