{"id":"https://openalex.org/W4404411134","doi":"https://doi.org/10.1109/tsmc.2024.3490553","title":"Iterative Learning Control Design for Iteration-Varying State-of-Charge Profiles of Electric Vehicle Batteries","display_name":"Iterative Learning Control Design for Iteration-Varying State-of-Charge Profiles of Electric Vehicle Batteries","publication_year":2024,"publication_date":"2024-11-15","ids":{"openalex":"https://openalex.org/W4404411134","doi":"https://doi.org/10.1109/tsmc.2024.3490553"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2024.3490553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2024.3490553","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-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/A5027482001","display_name":"\u0110\u00ecnh H\u00f2a Nguy\u1ec5n","orcid":"https://orcid.org/0000-0003-3318-737X"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Dinh Hoa Nguyen","raw_affiliation_strings":["International Institute for Carbon-Neutral Energy Research (WPI-I2CNER) and the Institute of Mathematics for Industry, Kyushu University, Fukuoka, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3318-737X","affiliations":[{"raw_affiliation_string":"International Institute for Carbon-Neutral Energy Research (WPI-I2CNER) and the Institute of Mathematics for Industry, Kyushu University, Fukuoka, Japan","institution_ids":["https://openalex.org/I135598925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5027482001"],"corresponding_institution_ids":["https://openalex.org/I135598925"],"apc_list":null,"apc_paid":null,"fwci":1.1491,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77485066,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"55","issue":"1","first_page":"805","last_page":"816"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.9951000213623047,"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":0.9951000213623047,"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/T11749","display_name":"Iterative Learning Control Systems","score":0.9818000197410583,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10175","display_name":"Advanced DC-DC Converters","score":0.9763000011444092,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/iterative-learning-control","display_name":"Iterative learning control","score":0.8215134143829346},{"id":"https://openalex.org/keywords/state-of-charge","display_name":"State of charge","score":0.6631304025650024},{"id":"https://openalex.org/keywords/electric-vehicle","display_name":"Electric vehicle","score":0.6088568568229675},{"id":"https://openalex.org/keywords/charge-control","display_name":"Charge control","score":0.5649738907814026},{"id":"https://openalex.org/keywords/charge","display_name":"Charge (physics)","score":0.537399411201477},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.45877987146377563},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4579010307788849},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.43982088565826416},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4291017949581146},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.4214574098587036},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4168877601623535},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.4165685772895813},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2288210690021515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2210095226764679},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.18635866045951843},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.17372268438339233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1318964958190918},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.12525570392608643},{"id":"https://openalex.org/keywords/thermodynamics","display_name":"Thermodynamics","score":0.06959223747253418}],"concepts":[{"id":"https://openalex.org/C117619785","wikidata":"https://www.wikidata.org/wiki/Q6094414","display_name":"Iterative learning control","level":3,"score":0.8215134143829346},{"id":"https://openalex.org/C2776582896","wikidata":"https://www.wikidata.org/wiki/Q5368536","display_name":"State of charge","level":4,"score":0.6631304025650024},{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.6088568568229675},{"id":"https://openalex.org/C2777681924","wikidata":"https://www.wikidata.org/wiki/Q5074262","display_name":"Charge control","level":4,"score":0.5649738907814026},{"id":"https://openalex.org/C188082385","wikidata":"https://www.wikidata.org/wiki/Q73792","display_name":"Charge (physics)","level":2,"score":0.537399411201477},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.45877987146377563},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4579010307788849},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.43982088565826416},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4291017949581146},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.4214574098587036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4168877601623535},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.4165685772895813},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2288210690021515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2210095226764679},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.18635866045951843},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17372268438339233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1318964958190918},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.12525570392608643},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.06959223747253418},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsmc.2024.3490553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2024.3490553","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8299999833106995}],"awards":[{"id":"https://openalex.org/G5204132317","display_name":"Electrothermal iterative learning control and optimization of electric vehicle operation","funder_award_id":"23K03906","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1556990916","https://openalex.org/W1601553642","https://openalex.org/W1949318025","https://openalex.org/W1954918717","https://openalex.org/W1975274761","https://openalex.org/W2039808384","https://openalex.org/W2052848225","https://openalex.org/W2078896274","https://openalex.org/W2103787878","https://openalex.org/W2118993398","https://openalex.org/W2138099152","https://openalex.org/W2154971535","https://openalex.org/W2162673530","https://openalex.org/W2163322659","https://openalex.org/W2296108298","https://openalex.org/W2334134865","https://openalex.org/W2345184888","https://openalex.org/W2593630474","https://openalex.org/W2595564021","https://openalex.org/W2777635217","https://openalex.org/W2794612233","https://openalex.org/W2795311922","https://openalex.org/W2805977334","https://openalex.org/W2902792107","https://openalex.org/W2904574225","https://openalex.org/W2904691792","https://openalex.org/W2919564738","https://openalex.org/W2946956215","https://openalex.org/W2967502299","https://openalex.org/W2967763175","https://openalex.org/W2991546672","https://openalex.org/W3041846829","https://openalex.org/W4200382154","https://openalex.org/W4214691593","https://openalex.org/W4238160257","https://openalex.org/W4250589301","https://openalex.org/W4289768831","https://openalex.org/W4289768846","https://openalex.org/W4380883425","https://openalex.org/W4385235107","https://openalex.org/W4390494165","https://openalex.org/W4395054359","https://openalex.org/W6622423486"],"related_works":["https://openalex.org/W4296426226","https://openalex.org/W2009545949","https://openalex.org/W2129858636","https://openalex.org/W2391748216","https://openalex.org/W2373022960","https://openalex.org/W2013885801","https://openalex.org/W2344401273","https://openalex.org/W119413178","https://openalex.org/W4324118683","https://openalex.org/W2978389667"],"abstract_inverted_index":{"In":[0,170],"this":[1],"research,":[2],"a":[3,35,101,160,165],"battery":[4],"control":[5,31,48,91,185,197],"method":[6,26,103],"is":[7,85,112,138,190],"proposed":[8,25,113,151,195],"to":[9,50,75,87,114],"handle":[10],"the":[11,61,64,67,89,106,116,120,125,129,142,145,150,171,177,194,209,214,217,222],"repetitive":[12],"but":[13],"nonidentical":[14],"daily":[15],"state-of-charge":[16],"(SoC)":[17],"profiles":[18,127],"of":[19,66,175,216],"electric":[20],"vehicle":[21],"(EV)":[22],"batteries.":[23],"The":[24,134],"employs":[27],"an":[28,76],"iterative":[29],"learning":[30],"(ILC)":[32],"framework":[33],"having":[34],"quadratic":[36],"performance":[37],"index":[38],"with":[39,53],"iteration-varying":[40,46,54,77,178],"weighting":[41,179],"matrices.":[42],"This":[43,82],"results":[44],"in":[45,119,128],"ILC":[47,90,146,196,204],"gains":[49],"better":[51],"cope":[52],"SoC":[55,117,126,136,218],"profiles.":[56],"Moreover,":[57],"input":[58,92],"constraints":[59],"representing":[60],"limits":[62],"on":[63,105,124,213,221],"ranges":[65],"charge":[68],"and":[69,131,163,183,202],"discharge":[70],"currents":[71],"are":[72,153,181,187],"considered,":[73],"leading":[74],"constrained":[78],"convex":[79],"optimization":[80,83],"problem.":[81,99],"problem":[84],"solved":[86],"obtain":[88],"update":[93],"via":[94],"resolving":[95],"its":[96],"Lagrange":[97],"dual":[98],"Next,":[100],"data-driven":[102],"based":[104,123,220],"dynamic":[107],"mode":[108],"decomposition":[109],"(DMD)":[110],"approach":[111],"predict":[115],"profile":[118,137,219],"next":[121],"weekday":[122],"current":[130],"previous":[132],"weekdays.":[133],"predicted":[135],"then":[139],"served":[140],"as":[141,206,208],"reference":[143],"for":[144,159,164],"tracking":[147,215],"controller.":[148],"Finally,":[149],"methods":[152],"verified":[154],"through":[155],"extensive":[156],"numerical":[157],"simulations":[158],"synthetic":[161],"case":[162],"realistic,":[166],"benchmark":[167],"driving":[168,225],"pattern.":[169,226],"simulations,":[172],"different":[173],"ways":[174],"selecting":[176],"matrices":[180],"introduced":[182],"their":[184],"performances":[186],"compared.":[188],"It":[189],"also":[191],"shown":[192],"that":[193],"design":[198],"outperforms":[199],"conventional":[200],"P-type":[201],"adaptive":[203],"controllers":[205],"well":[207],"classical":[210],"proportional-integral-derivative":[211],"controller":[212],"considered":[223],"realistic":[224]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}