A Primary Full-Integrated Active Filter Auxiliary Power Module in Electrified Vehicles With Single-Phase Onboard Chargers
Bibliographic record
Abstract
In single-phase ac high-voltage (HV) battery chargers, as the input current is enforced to be varying sinusoidally in phase with the input voltage, the pulsating power at two times of the line frequency will be seen on the dc-link. Bulky capacitor bank or extra active filter (AF) circuits are needed to assimilate this harmonic current, which become a major barrier in terms of power density and cost. Sinusoidal charging method can be applied, while this might affect the charging efficiency and a deep study is still needed to further investigate on the impact to the Lithium-ion battery. An active filter auxiliary power module (AFAPM) based dual-mode dual-voltage charging system for vehicle application has been proposed. The AFAPM converter has two modes: the HV active filtering mode, in which the vehicle is connected to the grid and the converter assimilates the significant second-order harmonic current; and the low-voltage (LV) battery charging mode, in which the vehicle is running and the converter charges the LV battery from HV battery. However, a relay and inductors are still required in that converter to achieve the dual-mode operation. This paper proposes a primary full-integrated AFAPM for electrified vehicle applications with single-phase onboard chargers. The proposed AFAPM converter is composed of a two-phase bidirectional buck converter to work as an AF and a dual-active-bridge to operate as a LV battery charger auxiliary power module (APM). With the proposed converter, only an extra active energy storage capacitor is needed to achieve the active filtering. All the switches and inductors on the primary stage are shared between the AF and APM. Therefore, the use of a bulky capacitor bank or an additional AF circuit is avoided and, thus, the cost, size, and weight of the dual-voltage charging system in the electrified vehicle applications can be reduced. A 720-W prototype has been built to confirm the effectiveness of the proposed 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".