{"id":"W4410989852","doi":"10.1016/j.energy.2025.136953","title":"An improved Transformer incorporating fuzzy information entropy and average input strategy for SOC estimation of lithium-ion battery","year":2025,"lang":"en","type":"article","venue":"Energy","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canada's Ocean Supercluster; Chongqing Municipal Education Commission; Chongqing Science and Technology Commission; Liverpool School of Tropical Medicine","keywords":"Fuzzy logic; Transformer; Lithium-ion battery; Entropy (arrow of time); Ion; Automotive engineering; Computer science; Chemistry; Engineering; Battery (electricity); Electrical engineering; Thermodynamics; Physics; Artificial intelligence; Voltage; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008990138,0.0001039416,0.000127989,0.0002095986,0.00004958317,0.00003709539,0.00009968893,0.0001092405,0.000003639152],"category_scores_gemma":[0.00003278109,0.0001050007,0.00002164104,0.000170072,0.00003793617,0.000850227,0.00001405858,0.00009647789,4.328112e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005532351,"about_ca_system_score_gemma":0.00002298445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002073951,"about_ca_topic_score_gemma":0.00001230991,"domain_scores_codex":[0.9993926,0.00001107611,0.0002654047,0.00009187014,0.00007737533,0.0001616926],"domain_scores_gemma":[0.9996778,0.00005394329,0.00004404133,0.0001489514,0.00005216666,0.00002312967],"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":[0.00002807225,0.00001094092,0.00005095169,0.0002606171,0.00002253324,2.116216e-7,0.00009729663,0.3861983,0.1387276,0.01045982,0.00006635409,0.4640773],"study_design_scores_gemma":[0.0004083617,0.0001148139,0.0002034952,0.00003068573,0.000005117354,7.136309e-7,0.0001116663,0.6993033,0.2898766,0.009304206,0.0005432746,0.00009775151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1318144,0.00005120484,0.8667054,0.00007071675,0.0000735708,0.000156585,0.0000170266,0.0001944879,0.0009166449],"genre_scores_gemma":[0.9910234,0.00004366273,0.008661081,0.00003511674,0.00001446461,0.00007591001,0.0001058937,0.0000106117,0.00002983053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.859209,"threshold_uncertainty_score":0.4281804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008635089995340758,"score_gpt":0.254190000518475,"score_spread":0.2455549105231342,"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."}}