{"id":"W2131138176","doi":"10.1109/apec.2008.4522734","title":"Efficiency analysis of hybrid electric vehicle (HEV) traction motor-inverter drive for varied driving load demands","year":2008,"lang":"en","type":"article","venue":"Conference proceedings/Conference proceedings - IEEE Applied Power Electronics Conference and Exposition","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Automotive engineering; Traction motor; Electric vehicle; Traction (geology); Inverter; Hybrid vehicle; Traction control system; Motor drive; Computer science; Engineering; Electrical engineering; Voltage; Mechanical engineering; Power (physics); Physics","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":[0.0002796625,0.0002793963,0.0005133565,0.0006742201,0.0001980082,0.00030404,0.0004777987,0.000226611,0.00121187],"category_scores_gemma":[0.0006921036,0.0001544252,0.000251206,0.0004064878,0.0001442266,0.0003922954,0.0001996058,0.0001330483,0.0002909575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004109306,"about_ca_system_score_gemma":0.0001157085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002989918,"about_ca_topic_score_gemma":0.002267413,"domain_scores_codex":[0.9997844,0.00003101866,0.0000147295,0.00003546184,0.0001064892,0.00002796445],"domain_scores_gemma":[0.9996414,0.0001787111,0.00002607712,0.00003483889,0.000110732,0.000008230132],"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":[0.002185479,0.0004347705,0.05543618,0.0003654089,0.0002187532,0.0005377996,0.0004528415,0.5517461,0.2509622,0.001289534,0.001012418,0.1353586],"study_design_scores_gemma":[0.00004253405,0.0009715633,0.07553834,0.000009421955,0.00007352372,0.00017845,0.0001830448,0.8039855,0.1169033,0.0004331102,0.00164897,0.00003230747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866926,0.00006560251,0.0110274,0.00001309156,0.000001914333,0.00001446608,0.0001233924,0.0001190169,0.001942521],"genre_scores_gemma":[0.9985721,0.00002606429,0.0006671672,0.000002043397,6.344253e-7,0.000008103183,0.0001328347,0.0000142794,0.0005768451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002989918,"threshold_uncertainty_score":0.005945027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158944826059272,"score_gpt":0.2087323703393518,"score_spread":0.1971429220787591,"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."}}