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Record W2962650318

Switched capacitor converters:a new approach for high power applications

2016· dissertation· en· W2962650318 on OpenAlexaboutno aff
Hassan Taghizadeh Esfanjani

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsnot available
Fundersnot available
KeywordsConvertersElectrical engineeringEngineeringElectronic engineeringHigh voltagePower (physics)Boost converterVoltageSwitched capacitorCapacitorComputer sciencePhysics
DOInot available

Abstract

fetched live from OpenAlex

High-power, high-voltage and high voltage-conversion ratio DC-DC converters are an enabling technology for offshore DC grids of the future. These converters are required to interface between offshore wind farms and an offshore DC grid and a key design issue is the size and weight of the converter, which significantly impacts the cost of the associated off-shore platform. In addition to this application, some rural communities, particularly in Canada, Australia and South Africa,which are located far away from the electrical power generators, can take the advantages of this technology by tapping into existing HVDC transmission line using a high voltage-conversion ratio DC-DC converter. The work described in this thesis is an investigation as to how such DC-DC converters may be realised for these applications. First a review of existing DC-DC converters was carried out to assess their suitability for the target applications. A classification of DC-DC converters into Direct and Indirect converters was proposed in this work based on the manner in which the energy is transferred from the input to the output terminal of the converter. Direct DC-DC converters, particularly Switched Capacitor(SC) converters are more promising for high-voltage, high-power and high voltage-conversion ratio applications, since the converter can interface between the low-voltage and the high-voltage terminals using low-voltage and low-power power electronic modules. Existing SC topologies were examined to identify the most promising candidate circuits for the target applications. Four SC synthesis techniques were proposed in order to derive new SC circuits from existing topologies. A new 2-Leg Ladder, modular 2-Leg Ladder and bi-pole 2-Leg Ladder were devised, which had significant benefits in terms of size and weight when compared with existing circuits. A scaled power 1 kW converter was built in the laboratory in order to validate the analysis and compare the performance of the new 2-Leg ladder circuit against a conventional Ladder circuit, where it was shown that the new circuit had higher efficiency, smaller size and lower output voltage ripple than the Ladder converter.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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.

Opus teacher head0.009
GPT teacher head0.229
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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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