{"id":"W4388265603","doi":"10.3934/electreng.2023019","title":"Sliding mode control rotor flux MRAS based speed sensorless induction motor traction drive control for electric vehicles","year":2023,"lang":"en","type":"article","venue":"AIMS Electronics and Electrical Engineering","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"MRAS; Control theory (sociology); Estimator; Vector control; Controller (irrigation); Traction (geology); Torque; Computer science; Lyapunov function; Electronic speed control; Engineering; Rotor (electric); Control engineering; Induction motor; Voltage; Mathematics; Control (management)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000496326,0.0006632432,0.0008268728,0.001072651,0.0002569711,0.0001606984,0.0002430876,0.0004415777,0.000008102023],"category_scores_gemma":[0.0003628079,0.0007320445,0.0002891061,0.001717462,0.00001690907,0.0003189957,0.00001070321,0.0009242998,0.00001861344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007366437,"about_ca_system_score_gemma":0.0001208322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001967397,"about_ca_topic_score_gemma":0.000005377176,"domain_scores_codex":[0.9962318,0.00006068376,0.0006808923,0.0006876888,0.0004484059,0.001890532],"domain_scores_gemma":[0.9979578,0.001095265,0.000119972,0.0003214748,0.0001666599,0.0003388529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001883361,0.00003133707,0.00007404745,0.00008101256,0.0002338788,0.000008334572,0.00001930865,0.3596174,0.6275724,0.001464188,0.0003510023,0.01035878],"study_design_scores_gemma":[0.003975239,0.0005187513,0.001170095,0.00002858859,0.0001868688,0.00002626239,0.000005711671,0.9418186,0.04912693,0.0002063778,0.002210123,0.0007264507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8042319,0.002281604,0.1879241,0.0003181128,0.0004821635,0.002263575,0.0000460416,0.002398868,0.0000536426],"genre_scores_gemma":[0.997793,0.0003425887,0.000320854,0.0001133436,0.0006254149,0.0004030017,0.00005996142,0.0002428175,0.00009903843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5822012,"threshold_uncertainty_score":0.9995131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007468007669343396,"score_gpt":0.2093570281231986,"score_spread":0.2018890204538553,"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."}}