Saliency-based Speed Sensorless Control of Single-Inverter Dual Induction Machines using Reduced Amount of Current Sensors
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Bibliographic record
Abstract
Parallel supply of dual-motors by single-inverter is a frequent practice, especially in traction applications. Model-based sensorless drives mostly rely on four current sensors, two of which attached to each motor. In the medium to high speed range, these model-based strategies can calculate the flux and torque share of each motor since the inverter output voltage is relatively linear. However, zero electrical speed operation turns out to be unstable as the system becomes unobservable. This area can be covered by injection strategies. This paper applies the voltage step excitation sensorless concept to dual-motor drives, which has not been researched in literature to the best of author's knowledge. Besides, a novel current sensor configuration is presented, using only three (instead of four) current sensors. Thereby, phase A and B currents of one motor (M1) will be measured, while the third sensor is attached to phase C of M2. As will be shown, new sensor arrangement allows for separation of individual machines inherent saliencies and thus delivers information of both machines rotor position, enabling a correct motor torque/flux share calculation by means of FOC equations. Experimental results prove the functionality of the new sensor configuration and voltage step excitation strategy applied to two parallel-connected induction motors.
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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) | 0.001 | 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 | 0.000 |
| 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.
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