A Modeling Technique to Analyze the Impact of Inverter Supply Voltage and Cable Length on Industrial Motor-Drives
Bibliographic record
Abstract
This paper presents a precise modeling technique to evaluate the impact of high frequency overvoltage in long cable pulsewidth modulation drives. This modeling technique results from the need to correlate the inverter's supply voltage and cable length with the motor's dielectric insulation class. The mathematical formulas describing the transient voltage and current in the cable are developed in the frequency domain. The inverse Laplace transform of the voltage is then applied to obtain the time domain sets of equations for the computation of the overvoltage not only at the motor terminals, but at any point along the cable. The proposed technique is precise and very suitable to adjustable speed drive (ASD) systems. Contrary to existing methods, it does not require any representation of the ASD-system components. This paper includes simulations and experiments that were carried out on an industrial 5 kVA ASD prototype using a four-wire braided-shielded long cable. The measurements of the cable, inverter and motor required characteristics are investigated in detail. The simulation results are then compared with the obtained experimental waveforms so as to validate the modeling technique. At the end, some recommendations, aimed at protecting the motor, are formulated based upon the proposed technique.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".