{"id":"W2967075876","doi":"10.3390/su11164317","title":"A Bidirectional Power Charging Control Strategy for Plug-in Hybrid Electric Vehicles","year":2019,"lang":"en","type":"article","venue":"Sustainability","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Plug-in; State of charge; Automotive engineering; Diesel generator; MATLAB; Voltage; Grid; Hybrid power; Engineering; Power (physics); Electric vehicle; Automatic frequency control; Computer science; Electrical engineering; Battery (electricity); Diesel fuel","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002051573,0.0004648509,0.0002688071,0.00028716,0.0003447467,0.0005216331,0.0004437651,0.0002137414,0.001421146],"category_scores_gemma":[0.0002846623,0.0001188167,0.0002345588,0.0002025881,0.0002008084,0.0002547741,0.0004464815,0.0002923152,0.0002093357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002482422,"about_ca_system_score_gemma":0.0004017961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003728791,"about_ca_topic_score_gemma":0.003799753,"domain_scores_codex":[0.9998677,0.00002223538,0.000008456966,0.00002957777,0.00004577098,0.00002629389],"domain_scores_gemma":[0.9998879,0.00001902847,0.00002311966,0.000009265453,0.00004995504,0.00001066677],"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":[0.0004162829,0.0002819448,0.002050342,0.0002983982,0.00008662335,0.0004939294,0.0003622996,0.6231992,0.041448,0.02247818,0.003653658,0.3052311],"study_design_scores_gemma":[0.0000280616,0.0001926949,0.000603785,0.00001068063,0.00002005657,0.0000697183,0.00004413614,0.9906628,0.003567212,0.002485268,0.002302941,0.00001280803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07783942,0.0002624927,0.9023567,0.0001717095,0.0001286834,0.0001341305,0.00005087178,0.0007724439,0.01828349],"genre_scores_gemma":[0.9918948,0.00005805928,0.006365949,0.00002281329,0.00001080229,0.00003274098,0.00001851219,0.000009503684,0.001586881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003728791,"threshold_uncertainty_score":0.007414162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003228926837289473,"score_gpt":0.2102857332618771,"score_spread":0.2070568064245877,"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."}}