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Record W2966047744 · doi:10.1109/tec.2019.2932455

Step-Signal-Injection-Based Robust MTPA Operation Strategy for Interior Permanent Magnet Synchronous Machines

2019· article· en· W2966047744 on OpenAlex
Jinhui Xia, Yuanbo Guo, Ze Li, Juri Jatskevich, Xiaohua Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2019
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of British Columbia
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsControl theory (sociology)Robustness (evolution)AmpereTorqueSynchronous motorLyapunov functionRobust controlComputer scienceControl systemEngineeringCurrent (fluid)Nonlinear systemControl (management)Physics

Abstract

fetched live from OpenAlex

In various applications that utilize maximum torque per ampere (MTPA) operation of interior permanent magnet synchronous machines (IPMSMs), there exist unexpected perturbations in electrical parameters and operating environment, which deteriorate the accuracy and efficiency of the MTPA operation. This paper establishes a step-signal-injection-based robust MTPA operation strategy for the IPMSM drives. The method works by injecting a step signal into the current vector angle and observing the response in the current magnitude, followed by a proportional-integral controller which returns the system to optimal operation. The stability of the proposed algorithm is established using the Lyapunov theory. A speed-servo control system of IPMSM is considered, where a disturbance detection unit is designed to switch operation between optimal current angle updating mode and steady-state MTPA operation mode. Since the optimal current angle updating is independent of machine parameters, the impact of system perturbations on the MTPA operation can be effectively suppressed. Extensive experimental results for IPMSM and hardware-in-the-loop-based machine are presented to validate the effectiveness and robustness of the proposed method.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.196
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it