{"id":"W3018271682","doi":"10.1109/epec47565.2019.9074781","title":"Performance Analysis of Coulomb Counting Approach for State of Charge Estimation","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Coulomb; State of charge; Battery (electricity); Computer science; Error analysis; Charge (physics); Estimation; Error detection and correction; Approximation error; State (computer science); Observational error; Current (fluid); Measurement uncertainty; Algorithm; Physics; Applied mathematics; Mathematics; Electrical engineering; Statistics; Engineering; Quantum mechanics; Power (physics)","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":[0.004594289,0.001083497,0.001314207,0.001240551,0.0008425973,0.002053353,0.001581133,0.001413686,0.002339194],"category_scores_gemma":[0.02140375,0.0002460399,0.0004633587,0.001240683,0.0008651204,0.002206102,0.002035006,0.00104545,0.0005031727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476737,"about_ca_system_score_gemma":0.002299709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008414704,"about_ca_topic_score_gemma":0.003371421,"domain_scores_codex":[0.9970246,0.0008811679,0.0001221074,0.0003949752,0.001163276,0.0004140025],"domain_scores_gemma":[0.9891497,0.007475007,0.000715546,0.0005059579,0.001937582,0.0002161649],"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":[0.0006758551,0.0001304364,0.005479786,0.0002606563,0.0001210663,0.0002585125,0.0001621564,0.835541,0.005778649,0.03246275,0.00224066,0.1168885],"study_design_scores_gemma":[0.000004843088,0.00004411459,0.0002661549,0.0000118641,0.000009596075,0.00005357847,0.00001975329,0.996431,0.001458379,0.001470901,0.0002185698,0.00001126887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09241383,0.003548425,0.8885445,0.0006310311,0.0001824072,0.0001039618,0.0001553337,0.001475089,0.01294551],"genre_scores_gemma":[0.9494175,0.0009458683,0.04674562,0.0002189172,0.00007443177,0.00007950424,0.0002555893,0.0001000339,0.002162362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008414704,"threshold_uncertainty_score":0.02429718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01441942537615885,"score_gpt":0.2638402548423887,"score_spread":0.2494208294662298,"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."}}