Loss minimization of two stage solar powered speed sensorless vector controlled induction motor drive for water pumping
Bibliographic record
Abstract
This paper deals with a two stage solar photovoltaic (SPV) fed speed sensorless vector controlled induction motor drive (IMD) for water pumping system which is superior to conventional controlled motor as it is cheaper and reliable. One common practice is to estimate the flux from the terminal voltages and currents. The performance of the drive depends on the accuracy of the flux estimator. Usually the efficiency of the induction motor drive (IMD) is high around the rated load and deteriorates at partial loading. However, the efficiency can be enhanced by operating the motor at optimum flux by controlling the flux component of current. In this paper, a minimization technique is proposed to minimize the total losses to operate the drive at maximum efficiency. A modified perturb and observe (P&O) algorithm is used to track maximum power from SPV array. The smooth starting of the motor is attained by vector control of an induction motor. The system performance is simulated in MATLAB/Simulink environment and the results are compared with the conventional vector controlled IMD.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".