Bidirectional EV charger with ancillary power quality capabilities
Bibliographic record
Abstract
This paper presents a bidirectional electric vehicle (EV) charger with ancillary power quality (PQ) capabilities in grid-to-vehicle (G2V), vehicle-to-grid (V2G) and vehicle-to-home (V2H) applications. The proposed configuration consists of a five-level (5L) neutral point clamped (NPC) converter in cascaded with a dual-active half bridge (DAHB) DC-DC converter. The proposed cascaded control strategy used for regulating the common DC bus voltage as well as for compensating the grid current harmonics and the reactive power through the 5L-converter is based on a performant proportional-resonant (PR) compensator. By applying the single-phase-shift (SPS) technique to the DAHB converter, the battery power flow is accurately regulated. A detailed study with exhaustive tests and simulation results obtained in MATLAB-SimPowerSystems for a full-scale power system based on a Nissan Leaf´s battery validate the fairly good performance of the proposed configuration and control strategies. The main achievements of this work are: 1) the system’s stability is maintained even during fairly abrupt changing conditions, 2) in steady state of the G2V/V2G operation modes, the total harmonic distortion (THD) of the grid current remains below 3% while the power factor (PF) is kept at unity, 3) the reactive power demanded from the grid is zero in spite of feeding a highly nonlinear load, and 4) when a power outage occurs, the transition to the V2H mode is seamless and the home load is uninterruptedly supplied with a very low-distortion output voltage from the 5L-converter.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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".