Generalized State Space Average Model for Multi-Phase Interleaved Buck, Boost and Buck-Boost DC-DC Converters: Transient, Steady-State and Switching Dynamics
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Bibliographic record
Abstract
This paper presents a generalized state space average model (GSSAM) for multi-phase interleaved buck, boost and buck-boost converters. The GSSAM can model the switching behavior of the current and voltage waveforms, unlike the conventional average model which can model only the average value. The GSSAM is used for the converters with dominant oscillatory behavior such as resonant converters, high current ripple converters, and multi-converter systems. The maximum current and voltage through the system can be predicted by modeling the switching behavior of voltage and current. The GSSAM in the literature is introduced for single-phase converters only, and it is not introduced for multi-phase converters due to the high complexity associated with it. Hence, the GSSAM for multi-phase buck, boost and buck-boost converters are introduced in this paper and the proposed models can fit with converters of any number of phases. The number of operating phases in the multi-phase interleaved converters is proportional with the output power to achieve the maximum efficiency over the operating range. Therefore, the proposed GSSAMs can describe the operation at any number of operating phases with switching dynamics of phases. The proposed GSSAM is validated by comparing the transient and steady-state dynamics between the GSSAM and a switching model from PLECS.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it