A Direct Actual-Power Control Scheme for Current-Fed Dual-Active-Bridge DC/DC Converter Based on Virtual Impedance Estimation
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Bibliographic record
Abstract
High dynamic performance is an essential requirement for the dual-active-bridge (DAB) dc/dc converters. As dc voltage sources, they should maintain the desired output voltage instantly under all working conditions. However, the previous literature mainly focus on the dynamic control of the voltage-fed DAB converters, and the existing control schemes for the current-fed DAB converters achieve limited dynamic performance. Aiming at improving the dynamic performance, a direct actual-power control (DAPC) scheme based on virtual impedance estimation (VIE) is proposed for the current-fed DAB converters in this article. The proposed DAPC scheme is based on a parallel structure instead of the series structure of existing control schemes, and it realizes fast dynamic control through combining actual power control with the VIE method. The proposed DAPC scheme can obtain the fastest transient response for the output voltage without voltage overshoot in transient conditions, such as load step change, input voltage fluctuation, and the desired output voltage step change. Besides, a leakage inductor precharging method is integrated into the DAPC scheme to avoid the current mismatching. Finally, the proposed DAPC schemes are compared with two existing control schemes and tested in a scale-down experimental prototype. Experimental results verify the effectiveness of the proposed DAPC scheme.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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