Efficiency Improved Multi-Source Inverter for Hybrid Energy Storage Systems in Electric Vehicle Application
Bibliographic record
Abstract
Multisource inverters (MSIs) as a new approach for the integration of the energy and the power sources in electric vehicle applications have gained considerable attraction. Such structures offer the active control of the dc sources without using any dc/dc converters or magnetic elements, which reduces the weight, and the volume of the power electronics interface between the sources and the load. Moreover, high power density and improved efficiency due to the elimination of the magnetics are the other significant features of an MSI. This article proposes a novel three-phase MSI for integration and active control of a high-voltage dc source and a low-voltage dc source. The proposed MSI structure employs a smaller number of semiconductor devices at the current path in various operating modes in comparison to the previously published counterparts, which results in an improved efficiency operation. Performance of the proposed MSI using a modified space vector modulation technique for all possible operating modes is verified through simulations and experiments on a laboratory prototype
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".