{"id":"W4400119838","doi":"10.3390/en17133185","title":"Real-Time Implementable Integrated Energy and Cabin Temperature Management for Battery Life Extension in Electric Vehicles","year":2024,"lang":"en","type":"article","venue":"Energies","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"HVAC; Battery (electricity); Automotive engineering; Energy consumption; State of health; Computer science; Range (aeronautics); Energy management; Driving range; Simulation; Reliability engineering; Air conditioning; Power (physics); Engineering; Energy (signal processing); Electrical engineering; Mechanical engineering","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":[0.0001154172,0.000175113,0.0001760499,0.0004723104,0.00004575812,0.00009787612,0.0001376849,0.00009504263,0.00002946761],"category_scores_gemma":[0.0000212491,0.0001547373,0.00002765483,0.0005557477,0.00002570316,0.0001828716,0.0001062517,0.0001412296,0.000004662872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001459548,"about_ca_system_score_gemma":0.0000152546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005710488,"about_ca_topic_score_gemma":0.00003530411,"domain_scores_codex":[0.9989983,0.00001736515,0.0001887687,0.0002861313,0.0001141422,0.0003952316],"domain_scores_gemma":[0.9996151,0.0001196815,0.000008319568,0.0001995573,0.00001980313,0.00003752715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002831725,0.00001452077,0.00006633071,0.0003277693,0.00008447358,0.00008041724,0.00005223777,0.03733869,0.8481792,0.003143107,0.04561047,0.06507447],"study_design_scores_gemma":[0.001000031,0.0002191397,0.001613816,0.0004846463,0.00003538439,0.00002344917,0.001065941,0.2555291,0.6275135,0.005967851,0.1056781,0.0008690991],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992811,0.003994045,0.0007761261,0.0003280039,0.0001249835,0.000215448,0.00002360187,0.001126568,0.000600256],"genre_scores_gemma":[0.9877574,0.00640707,0.003539454,0.00005333382,0.00004641572,0.0002994074,0.00006536946,0.00006986723,0.001761666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2206657,"threshold_uncertainty_score":0.6310003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00805590649518931,"score_gpt":0.2475392546515522,"score_spread":0.2394833481563629,"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."}}