Internal Model Based Speed Estimation and Lyapunov Energy Function Based Control of a Surface Mount PMSM for Electric Vehicle Application
Bibliographic record
Abstract
In this paper, a speed sensing mechanism of a surface mount permanent magnet synchronous machine based on the internal model principle has been presented for an electric vehicle (EV) application. The current controller of the machine has been implemented adopting Lyapunov energy function based analysis so as to achieve global stability over the full range of operations. Performance of the proposed control come estimation architecture has been tested with an electric vehicle based application. The internal model based estimation determines the back emf of the machine and then by simple algebraic manipulations, the speed of the machine is calculated. An LC filter is connected at the machine terminals after the inverter to avoid impressing pulse width modulated voltage on the machine terminals so as to increase the life span of the machine. The proposed control come estimation architecture is verified via computer simulations using MATLAB/Simulink and PLECS domain and various case study results are presented to prove the efficacy of the control systems. Several case studies have been presented for the motoring as well as regenerative braking mode of the EV powertrain system.
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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) | 0.000 | 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)
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".