{"id":"W1494972600","doi":"10.1109/lescpe.2007.4437388","title":"Analysis of Flux Control for Wide Speed Range Operation of IPMSM Drive","year":2007,"lang":"en","type":"article","venue":"","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Vector control; Control theory (sociology); Electronic speed control; Digital signal processor; Torque; Digital signal processing; Range (aeronautics); Computer science; Flux (metallurgy); Magnetic flux; Field (mathematics); Machine control; Direct torque control; Motor drive; Operating speed; Synchronous motor; Limit (mathematics); Control (management); Control engineering; Engineering; Induction motor; Electrical engineering; Magnetic field; Voltage; Computer hardware; Materials science; Physics; Mathematics; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002617545,0.0003789777,0.0003904027,0.0005508906,0.0002485173,0.0005257088,0.0003073086,0.0003554168,0.002074173],"category_scores_gemma":[0.0008916678,0.0001183398,0.0002201949,0.0001689636,0.0002517795,0.0005398101,0.0001695227,0.0003243487,0.0002768254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002501188,"about_ca_system_score_gemma":0.000137535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004529601,"about_ca_topic_score_gemma":0.0002271415,"domain_scores_codex":[0.99968,0.00003390271,0.00001112025,0.00003873672,0.0002150826,0.00002114251],"domain_scores_gemma":[0.9997571,0.0001223611,0.00003018056,0.00001789842,0.00006664792,0.000005823952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005208164,0.0000976617,0.001661672,0.0007554124,0.00006911982,0.0005847925,0.0004569641,0.4065846,0.250181,0.04797641,0.001644349,0.2894672],"study_design_scores_gemma":[0.00001374542,0.0002369585,0.001861254,0.00002637454,0.00001469715,0.0002307733,0.00003066862,0.9614598,0.02728902,0.004627867,0.004190538,0.00001836474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07458903,0.0009003537,0.912222,0.0001251078,0.00003553725,0.00004737484,0.00003599911,0.0004979629,0.01154661],"genre_scores_gemma":[0.972737,0.000402509,0.02431407,0.00002601961,0.00003049681,0.00004887199,0.00003843382,0.00007951385,0.002323023],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002074173,"threshold_uncertainty_score":0.006938815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007304394883902081,"score_gpt":0.2240456173676873,"score_spread":0.2167412224837852,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}