{"id":"W3019059112","doi":"10.3233/jcm-204276","title":"Acceleration slip regulation control for four-wheel independently drive electric vehicle based on fuzzy control","year":2020,"lang":"en","type":"article","venue":"Journal of Computational Methods in Sciences and Engineering","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"CarSim; Acceleration; Slip (aerodynamics); Torque; Electric vehicle; Control theory (sociology); Automotive engineering; Slip ratio; Electronic stability control; Computer science; Fuzzy control system; Fuzzy logic; Slip angle; Range (aeronautics); Vehicle dynamics; Power (physics); Engineering; Control (management); Physics; Steering wheel","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":[0.0002362484,0.0004093214,0.0003581864,0.0002968031,0.0003884029,0.0005028218,0.0005104384,0.0002757443,0.0009015459],"category_scores_gemma":[0.0003325954,0.0001528821,0.00031555,0.0001708231,0.0002742391,0.0002290791,0.000317612,0.0003261894,0.0001147308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004118572,"about_ca_system_score_gemma":0.0003606213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0077945,"about_ca_topic_score_gemma":0.005645687,"domain_scores_codex":[0.9998494,0.0000162129,0.000009510662,0.00003397439,0.00006501131,0.00002589431],"domain_scores_gemma":[0.999861,0.00002803327,0.00002641612,0.000008550929,0.00006565382,0.00001028538],"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":[0.000610085,0.0001723494,0.002703539,0.0002967035,0.00008369311,0.0003625053,0.0002665574,0.7709496,0.0647754,0.006999627,0.001582826,0.151197],"study_design_scores_gemma":[0.00003787293,0.0002375317,0.001089563,0.000009983617,0.00002532062,0.00003790801,0.00002263379,0.9916499,0.005232501,0.000702905,0.000941491,0.00001251985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.230248,0.0005210146,0.7562132,0.0001486978,0.0001767668,0.00007983501,0.00005445277,0.0005953701,0.01196254],"genre_scores_gemma":[0.9929697,0.00007762263,0.005578765,0.00001546359,0.00001061953,0.00002562458,0.00001696734,0.000004171768,0.001301053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0077945,"threshold_uncertainty_score":0.01549828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02546401566225442,"score_gpt":0.2878950568622794,"score_spread":0.262431041200025,"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."}}