{"id":"W2329445690","doi":"10.1115/dscc2015-9723","title":"Battery Thermal Management of Electric Vehicles: An Optimal Control Approach","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Battery (electricity); Automotive engineering; PID controller; Controller (irrigation); Range (aeronautics); Computer science; Electric vehicle; Optimal control; Power (physics); Driving range; Energy management; Control theory (sociology); Control (management); Control engineering; Temperature control; Engineering; Energy (signal processing); Mathematical optimization; Mathematics","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":[0.000620255,0.0009471353,0.0009174751,0.0005155305,0.0003231465,0.001516643,0.0007514152,0.0009069887,0.00174578],"category_scores_gemma":[0.001053803,0.0003718288,0.0005981452,0.0004332152,0.0007035355,0.000773204,0.0006784161,0.0009087364,0.0002221525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006524418,"about_ca_system_score_gemma":0.0009025713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004842651,"about_ca_topic_score_gemma":0.002428122,"domain_scores_codex":[0.9996867,0.0001058136,0.00001517463,0.00006207774,0.00009761508,0.00003262973],"domain_scores_gemma":[0.9997874,0.000108069,0.00002857006,0.000007058853,0.00006036292,0.000008578289],"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":[0.00002890544,0.00005146263,0.0001542265,0.0001458015,0.00002837221,0.00004008571,0.0000367437,0.9619349,0.001415507,0.01417948,0.0005780494,0.02140654],"study_design_scores_gemma":[0.000008444837,0.00005088568,0.00008033287,0.00001499803,0.00001080711,0.000009280909,0.00001863757,0.9928901,0.0003040791,0.005603033,0.001003043,0.000006289738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009603535,0.002704767,0.972418,0.0005568429,0.0001471888,0.00006971023,0.00002642049,0.00008931172,0.0143843],"genre_scores_gemma":[0.9066514,0.00480074,0.07680969,0.0002983019,0.0003159427,0.0003041067,0.00006257532,0.00005414956,0.01070307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004842651,"threshold_uncertainty_score":0.009628892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02474671928197523,"score_gpt":0.2557109898862587,"score_spread":0.2309642706042835,"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."}}