{"id":"W4400351637","doi":"10.1109/gpecom61896.2024.10582640","title":"Control Strategy for Torque Ripple Reduction in Brushless DC Motors with 180-Degree Commutation","year":2024,"lang":"en","type":"article","venue":"","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Commutation; Control theory (sociology); DC motor; Torque ripple; Torque; Reduction (mathematics); Degree (music); Brushed DC electric motor; Direct torque control; Machine control; Ripple; Torque motor; Computer science; Control (management); Engineering; Control engineering; Mathematics; Electrical engineering; Physics; AC motor; Induction motor; Voltage; Artificial intelligence","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":[0.0002150273,0.0005337903,0.0004696836,0.0005524068,0.0003766743,0.0004930799,0.0006119346,0.0002211278,0.001061146],"category_scores_gemma":[0.0002931234,0.0001614999,0.000217483,0.0003919145,0.0002478654,0.0002439424,0.0002185125,0.0002460214,0.0002555894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002361635,"about_ca_system_score_gemma":0.0002972851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001364675,"about_ca_topic_score_gemma":0.001242349,"domain_scores_codex":[0.9998298,0.00002084514,0.00001864357,0.00003451551,0.00007979224,0.00001652798],"domain_scores_gemma":[0.9998609,0.00002331779,0.00003397659,0.00001455537,0.00005881551,0.000008533487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005941573,0.0003016036,0.0009255957,0.0006442972,0.00008226634,0.0003273217,0.0004904182,0.06941551,0.2720236,0.009784671,0.00215483,0.6432557],"study_design_scores_gemma":[0.000165675,0.0008382947,0.002183,0.00005339607,0.00008058477,0.0003851276,0.00009884078,0.8889927,0.09634137,0.002204621,0.008615089,0.00004136384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04778819,0.0006615586,0.9459163,0.00007526542,0.0000982667,0.0001009842,0.00001747866,0.0007426398,0.004599317],"genre_scores_gemma":[0.9243221,0.0002877106,0.0726573,0.00007579879,0.00003833687,0.0000823161,0.00003433563,0.00004324738,0.002458843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001364675,"threshold_uncertainty_score":0.003549874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01807340224856603,"score_gpt":0.2332514206165037,"score_spread":0.2151780183679377,"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."}}