A Multi-Source Inverter for Electric Drive Vehicles
Bibliographic record
Abstract
Traditionally, energy storage systems in electric drive vehicles can be connected to the high voltage DC link through passive or active configurations. Passive configuration puts sources in parallel without any decoupling converter among sources which increases the number of series cells in battery and Ultra-Capacitor (UC) bank. Also, due to the lack of control over UC, its stored energy cannot be utilized efficiently. Active configurations exploit DC/DC converters to control the sources separately. However, existence of DC/DC converters with bulk magnetics increases the system volume and weight, and decreases the efficiency due to inductors' series resistances. Recently, multisource inverters as a new concept in electric drive vehicle applications have been introduced. Higher efficiency due to single stage conversion and compact structures due to removal of the magnetics are of the advantages of such systems. In this paper, a modular multi-source inverter is proposed for combining battery packs and UC banks as the energy storage systems in electric drive vehicles. Matlab Simulink was used for simulation purposes and a scaled down lab prototype was built to verify the simulations.
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".