{"id":"W2796211202","doi":"10.1109/vppc.2017.8330985","title":"An Optimal Control-Based Strategy for Energy Management of Electric Vehicles Using Battery/Supercapacitor","year":2017,"lang":"en","type":"article","venue":"","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Canada Research Chairs; European Commission","keywords":"Energy management; Supercapacitor; Computer science; Battery (electricity); Optimal control; State of charge; Control engineering; Electric vehicle; Energy storage; Control (management); Automotive engineering; Energy (signal processing); Control theory (sociology); Mathematical optimization; Engineering; Power (physics); Artificial intelligence; Capacitance; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00009192371,0.000151565,0.0002153671,0.0001168932,0.0001488949,0.00007277078,0.00040143,0.00008188292,0.00001512433],"category_scores_gemma":[0.000005708983,0.000143558,0.00006605573,0.00006016479,0.00005042191,0.0002005435,0.00001232462,0.0000657615,8.550748e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004264806,"about_ca_system_score_gemma":0.00001447647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004410533,"about_ca_topic_score_gemma":0.000003299136,"domain_scores_codex":[0.9992096,0.000007570364,0.0001939516,0.0001676806,0.0001009667,0.0003202322],"domain_scores_gemma":[0.9993744,0.00003973694,0.00004873283,0.0004544978,0.00004398172,0.00003860743],"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":[0.0002013293,0.0001924125,0.002775517,0.0004352519,0.0005044137,0.00002791334,0.00001038283,0.3970822,0.3785747,0.02615192,0.0007417627,0.1933022],"study_design_scores_gemma":[0.0007387412,0.0001859411,0.001979935,0.00001480969,0.00004363868,0.000001502942,0.00002043393,0.7167596,0.2797991,0.0002203338,0.00007774535,0.0001581647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6968756,0.0002042172,0.3016689,0.00002408033,0.00004045691,0.0001381687,0.000008757842,0.0003491196,0.0006906963],"genre_scores_gemma":[0.9902015,0.00005025249,0.009580408,0.00002064361,0.00004882091,0.00003274772,0.000003156232,0.00003042213,0.00003209319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3196774,"threshold_uncertainty_score":0.5854124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365465293196072,"score_gpt":0.2550578458711024,"score_spread":0.2314031929391416,"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."}}