{"id":"https://openalex.org/W7154696056","doi":"https://doi.org/10.1109/lats70329.2026.11480359","title":"Adaptive Neural Network Optimization of Vehicle Start-Stop Systems Using Digital Twin Framework","display_name":"Adaptive Neural Network Optimization of Vehicle Start-Stop Systems Using Digital Twin Framework","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7154696056","doi":"https://doi.org/10.1109/lats70329.2026.11480359"},"language":null,"primary_location":{"id":"doi:10.1109/lats70329.2026.11480359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lats70329.2026.11480359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 27th Latin American Test Symposium (LATS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046882782","display_name":"George Flutur","orcid":null},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"George Flutur","raw_affiliation_strings":["Technical University of Cluj-Napoca,Department of Automation,Cluj-Napoca,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Cluj-Napoca,Department of Automation,Cluj-Napoca,Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133280684","display_name":"Ovidiu-Petru Stan","orcid":null},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Ovidiu-Petru Stan","raw_affiliation_strings":["Technical University of Cluj-Napoca,Department of Automation,Cluj-Napoca,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Cluj-Napoca,Department of Automation,Cluj-Napoca,Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068062123","display_name":"Gabriel Chindri\u0219","orcid":null},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Gabriel Chindris","raw_affiliation_strings":["Technical University of Cluj-Napoca,Department of Applied Electronics,Cluj-Napoca,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Cluj-Napoca,Department of Applied Electronics,Cluj-Napoca,Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030578513","display_name":"Liviu-Cristian MICLEA","orcid":null},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Liviu-Cristian Miclea","raw_affiliation_strings":["Technical University of Cluj-Napoca,Department of Automation,Cluj-Napoca,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Cluj-Napoca,Department of Automation,Cluj-Napoca,Romania","institution_ids":["https://openalex.org/I158333966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.54375213,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10808","display_name":"Electric and Hybrid Vehicle Technologies","score":0.3537999987602234,"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/T10808","display_name":"Electric and Hybrid Vehicle Technologies","score":0.3537999987602234,"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/T12095","display_name":"Vehicle emissions and performance","score":0.1111999973654747,"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/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.058400001376867294,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.5954999923706055},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.28380000591278076},{"id":"https://openalex.org/keywords/adaptive-control","display_name":"Adaptive control","score":0.28360000252723694},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.28299999237060547},{"id":"https://openalex.org/keywords/control-system","display_name":"Control system","score":0.2687000036239624}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6189000010490417},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5954999923706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39579999446868896},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.2881999909877777},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.28360000252723694},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.26910001039505005},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25999999046325684},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lats70329.2026.11480359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lats70329.2026.11480359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 27th Latin American Test Symposium (LATS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W135996379","https://openalex.org/W2018553794","https://openalex.org/W2087462124","https://openalex.org/W2295598076","https://openalex.org/W3037414163","https://openalex.org/W4220715364","https://openalex.org/W4366001283","https://openalex.org/W4379470750","https://openalex.org/W4388380101","https://openalex.org/W4398164319","https://openalex.org/W4401891402","https://openalex.org/W4409536747","https://openalex.org/W7152690653"],"related_works":[],"abstract_inverted_index":{"Building":[0],"upon":[1],"digital":[2,50],"twin":[3,51],"frameworks":[4],"for":[5,16,31,40,122],"battery":[6,81],"monitoring,":[7],"this":[8],"paper":[9],"introduces":[10],"an":[11],"adaptive":[12,56],"neural":[13],"network":[14],"approach":[15],"optimizing":[17],"vehicle":[18],"start-stop":[19,41],"systems.":[20],"The":[21,91,109],"proposed":[22],"ML-enhanced":[23],"framework":[24],"integrates":[25],"Long":[26],"Short-Term":[27],"Memory":[28],"(LSTM)":[29],"networks":[30],"State":[32],"of":[33],"Health":[34],"(SOH)":[35],"prediction":[36,71],"with":[37],"XGBoost-based":[38],"optimization":[39,102],"decision":[42],"making.":[43],"By":[44],"leveraging":[45],"continuous":[46],"feedback":[47],"from":[48],"the":[49,53],"model,":[52],"system":[54,92],"achieves":[55],"learning":[57],"capabilities":[58],"that":[59],"respond":[60],"to":[61,74],"individual":[62],"driving":[63],"patterns.":[64,108],"Experimental":[65],"results":[66],"demonstrate":[67],"significant":[68],"improvements:":[69],"SOH":[70],"accuracy":[72],"improved":[73],"1.82":[75],"%":[76,99],"mean":[77],"absolute":[78],"error,":[79],"while":[80,100],"life":[82],"extension":[83],"reached":[84],"<tex":[85],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[86],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{2":[87],"4.":[88],"2}":[89],"\\boldsymbol{\\%}$</tex>.":[90],"maintains":[93],"emission":[94],"reduction":[95],"benefits":[96],"above":[97],"92.3":[98],"adapting":[101],"thresholds":[103],"based":[104],"on":[105],"realworld":[106],"usage":[107],"edge-deployable":[110],"solution":[111],"requires":[112],"less":[113],"than":[114],"50":[115],"ms":[116],"inference":[117],"time,":[118],"making":[119],"it":[120],"suitable":[121],"real-time":[123],"automotive":[124],"applications.":[125]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-18T00:00:00"}