{"id":"https://openalex.org/W4415968436","doi":"https://doi.org/10.1109/iecon58223.2025.11221600","title":"Time-aware VAE offline reinforcement learning energy management for electric vehicles","display_name":"Time-aware VAE offline reinforcement learning energy management for electric vehicles","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W4415968436","doi":"https://doi.org/10.1109/iecon58223.2025.11221600"},"language":null,"primary_location":{"id":"doi:10.1109/iecon58223.2025.11221600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon58223.2025.11221600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2025 \u2013 51st Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100325779","display_name":"Fei Li","orcid":"https://orcid.org/0000-0001-8712-4898"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Li","raw_affiliation_strings":["Central South University,School of Automation,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,School of Automation,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110760465","display_name":"Yu Jiang","orcid":"https://orcid.org/0009-0005-6998-759X"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Jiang","raw_affiliation_strings":["Central South University,School of Automation,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,School of Automation,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100548988","display_name":"Yongcai Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongcai Ma","raw_affiliation_strings":["Central South University,School of Automation,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,School of Automation,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101826652","display_name":"Yue Wu","orcid":"https://orcid.org/0000-0002-7463-5397"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Wu","raw_affiliation_strings":["Central South University,School of Electronic Information,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,School of Electronic Information,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070458251","display_name":"Heng Li","orcid":"https://orcid.org/0000-0003-4434-254X"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Li","raw_affiliation_strings":["Central South University,School of Electronic Information,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,School of Electronic Information,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035958468","display_name":"Shilong Zhuo","orcid":"https://orcid.org/0000-0002-0599-6455"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilong Zhuo","raw_affiliation_strings":["Central South University,School of Computer Science and Engineering,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,School of Computer Science and Engineering,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10808","display_name":"Electric and Hybrid Vehicle Technologies","score":0.9591000080108643,"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":0.9591000080108643,"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/T10663","display_name":"Advanced Battery Technologies Research","score":0.015599999576807022,"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":0.00430000014603138,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8611999750137329},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7343000173568726},{"id":"https://openalex.org/keywords/energy-management","display_name":"Energy management","score":0.5932000279426575},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5616000294685364},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4869000017642975},{"id":"https://openalex.org/keywords/energy-management-system","display_name":"Energy management system","score":0.41920000314712524},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4180999994277954}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8611999750137329},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7343000173568726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6396999955177307},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.5932000279426575},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5616000294685364},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4869000017642975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4641999900341034},{"id":"https://openalex.org/C2781260460","wikidata":"https://www.wikidata.org/wiki/Q6139999","display_name":"Energy management system","level":4,"score":0.41920000314712524},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4180999994277954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3386000096797943},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.328900009393692},{"id":"https://openalex.org/C2776582896","wikidata":"https://www.wikidata.org/wiki/Q5368536","display_name":"State of charge","level":4,"score":0.3215000033378601},{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.31929999589920044},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.2872999906539917},{"id":"https://openalex.org/C73916439","wikidata":"https://www.wikidata.org/wiki/Q837718","display_name":"Energy storage","level":3,"score":0.26989999413490295},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2653999924659729},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon58223.2025.11221600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon58223.2025.11221600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2025 \u2013 51st Annual Conference of the IEEE Industrial Electronics Society","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":12,"referenced_works":["https://openalex.org/W2065788296","https://openalex.org/W2166080624","https://openalex.org/W2769605893","https://openalex.org/W2888142130","https://openalex.org/W2969601893","https://openalex.org/W4220768938","https://openalex.org/W4385372541","https://openalex.org/W4385888991","https://openalex.org/W4400405011","https://openalex.org/W4404226376","https://openalex.org/W4405632846","https://openalex.org/W4408728166"],"related_works":[],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,105,111,122,139,145,154],"limitations":[3],"of":[4,94,142,144,157],"traditional":[5],"energy":[6,11,56,112],"management":[7,57,113],"strategies":[8],"in":[9,26,160,171],"hybrid":[10],"storage":[12],"systems":[13],"for":[14,167],"electric":[15],"vehicles,":[16],"including":[17],"poor":[18],"adaptability":[19],"to":[20,78,89],"dynamic":[21,54],"conditions":[22],"and":[23,43,138],"safety":[24],"risks":[25],"online":[27],"reinforcement":[28,35],"learning,":[29],"this":[30],"paper":[31],"proposes":[32],"an":[33],"offline":[34],"learning":[36],"framework":[37],"integrating":[38],"a":[39,53,60,86,117,126,164],"time-aware":[40],"variational":[41,73],"autoencoder":[42,74],"Decision":[44,83],"Transformer.":[45],"Initially,":[46],"high-quality":[47],"expert":[48,128],"trajectories":[49,77],"are":[50],"generated":[51],"by":[52,136],"programming-based":[55],"strategy.":[58],"Subsequently,":[59],"bidirectional":[61],"long":[62],"short-term":[63],"memory":[64],"network":[65],"extracts":[66],"temporal":[67,92],"features":[68],"from":[69],"state":[70,141],"sequences,":[71,97],"while":[72],"synthesizes":[75],"physics-constrained":[76],"mitigate":[79],"distribution":[80],"shift.":[81],"Finally,":[82],"Transformer":[84],"employs":[85],"self-attention":[87],"mechanism":[88],"conduct":[90],"multiscale":[91],"modeling":[93],"historical":[95],"state-action":[96],"establishing":[98],"implicit":[99],"policy":[100],"mapping.":[101],"Experimental":[102],"results":[103],"under":[104],"Dallas5":[106],"driving":[107],"cycle":[108],"demonstrate":[109],"that":[110],"strategy":[114,123],"trained":[115,124],"with":[116,125],"mixed":[118],"dataset":[119,129],"D1":[120],"outperforms":[121],"pure":[127],"D2:":[130],"battery":[131],"capacity":[132],"loss":[133],"is":[134,147],"reduced":[135],"5.5%,":[137],"final":[140],"charge":[143],"supercapacitor":[146],"stably":[148],"maintained":[149],"at":[150],"0.7320.":[151],"This":[152],"highlights":[153],"critical":[155],"role":[156],"data":[158],"diversity":[159],"enhancing":[161],"generalization,":[162],"offering":[163],"novel":[165],"pathway":[166],"robust":[168],"EMS":[169],"design":[170],"real-world":[172],"vehicular":[173],"applications.":[174]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-06T00:00:00"}