{"id":"W1969016560","doi":"10.1115/esda2014-20599","title":"Performance Comparison of Different Power Management Control Strategies for a Hybrid Fuel Cell/Battery Vehicle","year":2014,"lang":"en","type":"article","venue":"","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Automotive engineering; Battery (electricity); Hybrid vehicle; Hybrid power; Energy management; Driving cycle; Hybrid system; Thermostat; Computer science; Power (physics); Regenerative brake; Internal combustion engine; Acceleration; Engineering; Electric vehicle; Energy (signal processing); Electrical engineering; Brake","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":[0.0003128737,0.0004475598,0.0003467212,0.0005024636,0.0002861802,0.000489696,0.0003187143,0.0002761429,0.001524387],"category_scores_gemma":[0.0004568778,0.0001162219,0.0002461913,0.0001926117,0.0001422485,0.0002508824,0.0001863652,0.0002016134,0.00019121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003129659,"about_ca_system_score_gemma":0.000257244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006024701,"about_ca_topic_score_gemma":0.003515716,"domain_scores_codex":[0.9998885,0.00001783761,0.00001010286,0.00001785705,0.00003961147,0.00002603533],"domain_scores_gemma":[0.9997725,0.00007504062,0.00002915486,0.00001380726,0.00009322671,0.00001624161],"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":[0.002496167,0.0008807557,0.009313179,0.0007189756,0.0002442926,0.0002735777,0.0003373761,0.6730679,0.09190527,0.001804678,0.001244337,0.2177135],"study_design_scores_gemma":[0.00009134052,0.001864313,0.006657045,0.00001933007,0.00007306621,0.00006119314,0.0001586341,0.9572863,0.03244548,0.0003077675,0.001010685,0.00002482638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9490864,0.0004103942,0.04000524,0.00009005713,0.00004143894,0.00008842069,0.00009294572,0.0004090606,0.009776187],"genre_scores_gemma":[0.9981489,0.00004449347,0.001279587,0.00000702498,0.000001448772,0.00001635792,0.0000312999,0.000003978098,0.0004668611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006024701,"threshold_uncertainty_score":0.01197922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005720137468137714,"score_gpt":0.1942943520190039,"score_spread":0.1885742145508661,"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."}}