{"id":"https://openalex.org/W7151384284","doi":"https://doi.org/10.1109/access.2026.3681620","title":"A Multi-Head Attention ResCNN\u2013BiGRU Model for Robust SOC Estimation in EVs Lithium-Ion Batteries Using Real-World Driving Data","display_name":"A Multi-Head Attention ResCNN\u2013BiGRU Model for Robust SOC Estimation in EVs Lithium-Ion Batteries Using Real-World Driving Data","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7151384284","doi":"https://doi.org/10.1109/access.2026.3681620"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3681620","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3681620","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3681620","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133114226","display_name":"N. Vigneswar","orcid":null},"institutions":[{"id":"https://openalex.org/I932239252","display_name":"SASTRA University","ror":"https://ror.org/032jk8892","country_code":"IN","type":"education","lineage":["https://openalex.org/I932239252"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"N. Vigneswar","raw_affiliation_strings":["Department of Mathematics, School of Arts, Sciences, Humanities, and Education (SASHE), Artificial Intelligence, Energy, and Control Systems (AIE and CS) Laboratory, SASTRA University, Thanjavur, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0002-6096-6582","affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Arts, Sciences, Humanities, and Education (SASHE), Artificial Intelligence, Energy, and Control Systems (AIE and CS) Laboratory, SASTRA University, Thanjavur, Tamil Nadu, India","institution_ids":["https://openalex.org/I932239252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047742970","display_name":"R. Manivannan","orcid":"https://orcid.org/0000-0003-4212-1305"},"institutions":[{"id":"https://openalex.org/I932239252","display_name":"SASTRA University","ror":"https://ror.org/032jk8892","country_code":"IN","type":"education","lineage":["https://openalex.org/I932239252"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Manivannan","raw_affiliation_strings":["Department of Mathematics, School of Arts, Sciences, Humanities, and Education (SASHE), Artificial Intelligence, Energy, and Control Systems (AIE and CS) Laboratory, SASTRA University, Thanjavur, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0003-4212-1305","affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Arts, Sciences, Humanities, and Education (SASHE), Artificial Intelligence, Energy, and Control Systems (AIE and CS) Laboratory, SASTRA University, Thanjavur, Tamil Nadu, India","institution_ids":["https://openalex.org/I932239252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077769370","display_name":"Chala Merga Abdissa","orcid":"https://orcid.org/0000-0003-3685-4887"},"institutions":[{"id":"https://openalex.org/I4210129636","display_name":"Addis Ababa Science and Technology University","ror":"https://ror.org/02psd9228","country_code":"ET","type":"education","lineage":["https://openalex.org/I4210129636"]},{"id":"https://openalex.org/I4537092","display_name":"Addis Ababa University","ror":"https://ror.org/038b8e254","country_code":"ET","type":"education","lineage":["https://openalex.org/I4537092"]}],"countries":["ET"],"is_corresponding":false,"raw_author_name":"Chala Merga Abdissa","raw_affiliation_strings":["School of Electrical and Computer Engineering (SECE), Addis Ababa Institute of Technology, Addis Ababa, Ethiopia"],"raw_orcid":"https://orcid.org/0000-0003-3685-4887","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering (SECE), Addis Ababa Institute of Technology, Addis Ababa, Ethiopia","institution_ids":["https://openalex.org/I4210129636","https://openalex.org/I4537092"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5133114226"],"corresponding_institution_ids":["https://openalex.org/I932239252"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.69448022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"54163","last_page":"54178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.870199978351593,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.870199978351593,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.03909999877214432,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10808","display_name":"Electric and Hybrid Vehicle Technologies","score":0.0284000001847744,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/system-on-a-chip","display_name":"System on a chip","score":0.41679999232292175},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.37400001287460327},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.36469998955726624},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.3529999852180481},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.2946000099182129},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.28380000591278076}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7150999903678894},{"id":"https://openalex.org/C118021083","wikidata":"https://www.wikidata.org/wiki/Q610398","display_name":"System on a chip","level":2,"score":0.41679999232292175},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.3869999945163727},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.35350000858306885},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3529999852180481},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2660999894142151}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3681620","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3681620","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:33e22fc95519486493c027a37cc963c0","is_oa":false,"landing_page_url":"https://doaj.org/article/33e22fc95519486493c027a37cc963c0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 54163-54178 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3681620","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3681620","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7476488351821899,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Precise":[0],"assessment":[1],"of":[2,5,17,33,161,194,202],"the":[3,12,29,87,91,113,159,162,166,173,180,205,233],"state":[4],"charge":[6],"(SOC)":[7],"is":[8,132,155],"essential":[9],"for":[10,104,237],"ensuring":[11],"safety,":[13],"efficiency,":[14],"and":[15,48,80,108,171,196,224],"dependability":[16],"electric":[18],"vehicles":[19],"(EVs).":[20],"However,":[21],"achieving":[22],"high":[23],"accuracy":[24],"remains":[25],"challenging":[26],"due":[27],"to":[28,97,157],"complex":[30],"nonlinear":[31],"characteristics":[32],"lithium-ion":[34],"batteries":[35],"(LIBs),":[36],"which":[37],"are":[38,122],"strongly":[39],"influenced":[40],"by":[41,164],"ambient":[42],"temperature":[43],"fluctuations,":[44],"dynamic":[45],"load":[46],"variations,":[47],"aging":[49],"effects.":[50],"To":[51],"address":[52],"these":[53],"challenges,":[54],"this":[55],"study":[56],"proposes":[57],"a":[58,81,147,188,197],"sophisticated":[59],"hybrid":[60,167],"deep":[61],"learning":[62,226],"(DL)":[63],"framework":[64,131,207],"that":[65,179],"combines":[66],"convolutional":[67],"neural":[68,213],"networks":[69,214],"(CNNs)":[70],"with":[71,146,170,187],"residual":[72,95],"connections":[73,96],"(ResCNN),":[74],"bidirectional":[75],"gated":[76,220],"recurrent":[77,221],"units":[78,222],"(Bi-GRU),":[79],"multi-head":[82],"attention":[83],"(MHA)":[84],"mechanism.":[85],"In":[86],"proposed":[88,206],"ResCNN-Bi-GRU-MHA":[89,181,234],"model,":[90],"ResCNN":[92],"layer":[93,115],"implements":[94],"strengthen":[98],"CNN-based":[99],"spatial":[100],"feature":[101,110],"extraction,":[102],"allowing":[103],"more":[105],"stable":[106],"training":[107],"richer":[109],"representations,":[111],"while":[112],"Bi-GRU":[114],"captures":[116],"temporal":[117],"dependencies;":[118],"subsequently,":[119],"both":[120],"features":[121],"dynamically":[123],"integrated":[124],"through":[125],"theMHAto":[126],"improve":[127],"prediction":[128],"accuracy.":[129],"The":[130,175],"validated":[133],"using":[134],"real-world":[135],"field":[136],"data":[137],"gathered":[138],"from":[139],"BMW":[140],"i3":[141],"EV":[142],"driving":[143],"trips":[144],"outfitted":[145],"60":[148],"Ah":[149],"LIB":[150],"pack.":[151],"A":[152],"comparative":[153],"analysis":[154],"performed":[156],"determine":[158],"influence":[160],"MHA":[163],"comparing":[165],"ResCNN-Bi-GRU":[168],"model":[169,182],"without":[172],"MHA.":[174],"established":[176],"results":[177],"demonstrate":[178],"achieves":[183],"superior":[184],"predictive":[185],"accuracy,":[186],"root":[189],"mean":[190,198],"squared":[191],"error":[192,200],"(RMSE)":[193],"6.0476%":[195],"absolute":[199],"(MAE)":[201],"4.5550%.":[203],"Furthermore,":[204],"outperforms":[208],"conventional":[209],"approaches,":[210],"including":[211],"feedforward":[212],"(FFNN),":[215],"long":[216],"short-term":[217],"memory":[218],"(LSTM),":[219],"(GRU),":[223],"extreme":[225],"machines":[227],"(ELM).":[228],"These":[229],"findings":[230],"point":[231],"out":[232],"model\u2019s":[235],"robustness":[236],"real-time":[238],"SOC":[239],"estimation":[240],"in":[241],"battery":[242],"management":[243],"systems":[244],"(BMS).":[245]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-04-08T00:00:00"}
