{"id":"W2797656919","doi":"10.1109/itec-india.2017.8333889","title":"Estimation of model parameters and state-of-charge for battery management system of Li-ion battery in EVs","year":2017,"lang":"en","type":"article","venue":"2017 IEEE Transportation Electrification Conference (ITEC-India)","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"State of charge; Battery (electricity); Extended Kalman filter; Estimator; Mean squared error; Kalman filter; Control theory (sociology); Voltage; Computer science; Schedule; Automotive engineering; Engineering; Mathematics; Electrical engineering; Statistics; Power (physics); Control (management); 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":[0.0003384113,0.0001910683,0.0003726574,0.0005050245,0.00007440735,0.00002928817,0.0003914436,0.0001308587,0.000002633352],"category_scores_gemma":[0.00003409082,0.00021794,0.00005480385,0.000153948,0.0001356924,0.0004829231,0.00000297434,0.0001581264,0.000001891142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008114836,"about_ca_system_score_gemma":0.00004421821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000201095,"about_ca_topic_score_gemma":0.00002321971,"domain_scores_codex":[0.9983935,0.0000204226,0.0007213186,0.0003000596,0.0002838763,0.0002807812],"domain_scores_gemma":[0.9985889,0.00009952636,0.0004879183,0.000602826,0.0001782327,0.00004258314],"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":[0.0002577811,0.000124707,0.005155003,0.005319126,0.0001401705,0.000004087035,0.001228366,0.4930097,0.3257934,0.003874864,0.00007860883,0.1650142],"study_design_scores_gemma":[0.000654628,0.00007200445,0.04125939,0.0002731806,0.00002900398,5.416933e-7,0.00008871049,0.5292121,0.4275072,0.0007288388,0.000003722419,0.0001706861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5370795,0.00002833095,0.4618236,0.00004267681,0.00005689155,0.0007074283,0.0001271194,0.00006253202,0.00007184356],"genre_scores_gemma":[0.991265,0.0003045995,0.00796767,0.000003309655,0.000004676439,0.0002624657,0.0001309759,0.00002773686,0.0000335918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4541855,"threshold_uncertainty_score":0.8887334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04236764197495717,"score_gpt":0.291684312677562,"score_spread":0.2493166707026048,"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."}}