{"id":"W4402693683","doi":"10.14447/jnmes.v27i2.a02","title":"An Efficient Li-ion Battery Management System with Lossless Charge Balancer for RUL and SoH Prediction","year":2024,"lang":"en","type":"article","venue":"Journal of New Materials for Electrochemical Systems","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Battery (electricity); Lossless compression; Ion; Computer science; Charge (physics); Chemistry; Physics; Artificial intelligence; Thermodynamics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002521569,0.0007088779,0.0007005088,0.0003383615,0.0006651011,0.000718132,0.001422066,0.0005924002,0.002342748],"category_scores_gemma":[0.0003370288,0.0002554388,0.0004038294,0.0003461899,0.0002141269,0.001186199,0.0006679018,0.0005933489,0.0008227351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005095425,"about_ca_system_score_gemma":0.0007305089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003979478,"about_ca_topic_score_gemma":0.003979971,"domain_scores_codex":[0.9997274,0.00001981459,0.00003005478,0.0001038721,0.00008557932,0.00003331066],"domain_scores_gemma":[0.999831,0.00001810733,0.00002412158,0.00002150502,0.00008949229,0.00001575264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001334655,0.0005500307,0.007555934,0.0006506594,0.0001849511,0.0008553054,0.0004400653,0.1526577,0.1574572,0.003230131,0.01847845,0.656605],"study_design_scores_gemma":[0.00007981839,0.0003793413,0.00160453,0.00002341106,0.00007330039,0.00023111,0.00004569452,0.9656978,0.02606359,0.0009407824,0.004819414,0.00004127932],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1597084,0.00253604,0.8087447,0.001084393,0.0006625626,0.0002638475,0.0005700534,0.01052981,0.01590027],"genre_scores_gemma":[0.9631581,0.0002868556,0.03038346,0.0003381101,0.0001058248,0.0001294139,0.0002951772,0.00003649033,0.005266523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003979478,"threshold_uncertainty_score":0.007912636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008625005758650972,"score_gpt":0.248230269599089,"score_spread":0.2396052638404381,"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."}}