{"id":"W1980361352","doi":"10.1016/j.enconman.2014.12.035","title":"Combination of Markov chain and optimal control solved by Pontryagin’s Minimum Principle for a fuel cell/supercapacitor vehicle","year":2014,"lang":"en","type":"article","venue":"Energy Conversion and Management","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":128,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières; Université de Moncton","funders":"","keywords":"Markov chain; Pontryagin's minimum principle; Control theory (sociology); Mathematical optimization; Optimal control; MATLAB; Block (permutation group theory); Markov model; Power (physics); Supercapacitor; Computer science; Mathematics; Control (management); Capacitance; Artificial intelligence; Chemistry","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":[0.001880899,0.0009859758,0.002269176,0.0008336962,0.0007350214,0.001191511,0.001085541,0.001801056,0.004336519],"category_scores_gemma":[0.003197747,0.001219414,0.001625908,0.0007418798,0.001348681,0.001285969,0.001428393,0.001707079,0.0002397582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486124,"about_ca_system_score_gemma":0.002693142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01421793,"about_ca_topic_score_gemma":0.01150171,"domain_scores_codex":[0.9994942,0.0001891619,0.00002303126,0.00008410036,0.0001186475,0.00009089334],"domain_scores_gemma":[0.9979827,0.001597283,0.0001052821,0.00005540642,0.0001922765,0.00006705367],"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":[0.00004259125,0.00003022962,0.000165603,0.00005691762,0.00003747148,0.00003587583,0.00002779796,0.9710173,0.0003209594,0.0238636,0.0004269144,0.003974796],"study_design_scores_gemma":[0.000006534437,0.000008252036,0.000046609,0.000003196442,0.000004715375,0.000003112431,0.00000265707,0.9942572,0.00005607762,0.005509895,0.00009804886,0.000003768244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02769873,0.0004362313,0.9589745,0.000632349,0.0001329731,0.00007327175,0.0001004448,0.0001407168,0.0118108],"genre_scores_gemma":[0.9136901,0.0003896334,0.07625934,0.0002408403,0.0001226663,0.0003288156,0.000171025,0.0001293255,0.008668228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01421793,"threshold_uncertainty_score":0.0282703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002726687824269322,"score_gpt":0.1668139602329292,"score_spread":0.1640872724086599,"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."}}