{"id":"W2767604027","doi":"10.1109/ias.2017.8101722","title":"State-of-charge estimation for li-ion battery using extended Kalman filter (EKF) and central difference Kalman filter (CDKF)","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Extended Kalman filter; Battery (electricity); State of charge; Control theory (sociology); Kalman filter; Voltage; Mean squared error; Invariant extended Kalman filter; Computer science; Approximation error; Engineering; Mathematics; Algorithm; Electrical engineering; Power (physics); Physics; Statistics; Artificial intelligence","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":[0.00007995569,0.0002252429,0.0002633908,0.0001492975,0.0002065327,0.0001137379,0.0003755893,0.0001064991,0.00009575081],"category_scores_gemma":[0.0001428319,0.0002040826,0.00005142477,0.00004632987,0.0001578759,0.000520568,0.0002186177,0.0001979486,0.000007352035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008356446,"about_ca_system_score_gemma":0.0000112363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002152762,"about_ca_topic_score_gemma":0.00001955891,"domain_scores_codex":[0.9986596,0.00001283439,0.0002836123,0.0002977414,0.0001850205,0.000561219],"domain_scores_gemma":[0.9990296,0.00009928743,0.0000879588,0.0006475962,0.00005441381,0.00008118863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001493374,0.0001218231,0.01229178,0.001368226,0.0001543581,0.00002348732,0.0004616706,0.02098763,0.521279,0.0006391608,0.00160429,0.4409193],"study_design_scores_gemma":[0.0005873365,0.00008793581,0.05522205,0.0001079019,0.00001249556,0.000008122558,0.00002479028,0.7137552,0.226737,0.002991011,0.0001518595,0.0003142633],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6825312,0.00004505822,0.3162943,0.0001151352,0.0001739137,0.0003650845,0.00004898862,0.0002218451,0.0002045169],"genre_scores_gemma":[0.9764109,0.00006126802,0.02295597,0.00002166642,0.00003795685,0.0000405659,0.00002231033,0.00004627018,0.0004030762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6927676,"threshold_uncertainty_score":0.8322246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04361774930574948,"score_gpt":0.3077139039226788,"score_spread":0.2640961546169294,"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."}}