{"id":"W2092200183","doi":"10.5402/2011/120351","title":"Estimation Strategies for the Condition Monitoring of a Battery System in a Hybrid Electric Vehicle","year":2011,"lang":"en","type":"article","venue":"ISRN Signal Processing","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Kalman filter; Robustness (evolution); Extended Kalman filter; Battery (electricity); Electric vehicle; Automotive engineering; Control theory (sociology); Condition monitoring; Computer science; Engineering; Particle filter; Power (physics); Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000165292,0.00009366092,0.0001204729,0.0001627927,0.00006597451,0.00003742353,0.0001754151,0.00004236753,0.000002742926],"category_scores_gemma":[0.00001796157,0.00007800291,0.00002263906,0.0002886164,0.00003667254,0.0004514968,0.00001847039,0.0001645314,0.000002129017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001158931,"about_ca_system_score_gemma":0.0000353502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008995271,"about_ca_topic_score_gemma":0.000001615376,"domain_scores_codex":[0.999286,0.00001086526,0.000217572,0.000112326,0.0001318627,0.000241362],"domain_scores_gemma":[0.9996626,0.0001155116,0.00005309647,0.000100964,0.00005487848,0.00001292274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006498351,0.00003116151,0.00251445,0.002095493,0.00002909107,0.00001153055,0.0007607359,0.1691453,0.2040218,0.0003473335,0.00001471493,0.6209635],"study_design_scores_gemma":[0.0001669494,0.00003962614,0.001682227,0.0002424328,0.000006696167,0.000005396224,0.001814303,0.7463449,0.2477303,0.001884114,0.000002463541,0.00008064527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4953059,0.0004018276,0.5036417,0.000005584759,0.000028706,0.000215587,0.000002307977,0.000209441,0.0001890174],"genre_scores_gemma":[0.9969087,0.000007663727,0.00288164,0.000001713446,0.00002584283,0.0001487216,0.000001491406,0.00002205758,0.000002127505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6208828,"threshold_uncertainty_score":0.3180866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03357398038346488,"score_gpt":0.2820849372516553,"score_spread":0.2485109568681905,"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."}}