A New Fault-Tolerant Technique Based on Nonsymmetrical Selective Harmonic Elimination for Cascaded H-Bridge Motor Drives
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Bibliographic record
Abstract
This article proposes a new fault-tolerant technique to increase the maximum balanced line-to-line output voltage of the cascaded H-bridge (CHB) motor drives. The CHB converters have been widely used for medium-voltage motor drives due to their scalability and reliability features. A significant indicator of the reliability is the maximum balanced line-to-line voltage amplitude under fault conditions. This article adopts a nonsymmetrical selective harmonic elimination (SHE) formulation to further extend the output voltage range with a good harmonic profile under fault conditions. The dc current component can be regulated for the dynamic braking operation. Based on the nonsymmetrical SHE formulation, the fault-tolerant problem that achieves the maximum output voltage range and good harmonic profile is converted to an optimization problem, which can be solved by the proposed optimization framework. By properly selecting the output voltage waveforms, the entire converter voltage capability can be achieved under fault conditions with a good harmonic profile. The performance of the proposed method is evaluated experimentally on a seven-level CHB motor drive.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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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