{"id":"https://openalex.org/W3033556475","doi":"https://doi.org/10.1109/tvt.2020.2999263","title":"Cross-Type Transfer for Deep Reinforcement Learning Based Hybrid Electric Vehicle Energy Management","display_name":"Cross-Type Transfer for Deep Reinforcement Learning Based Hybrid Electric Vehicle Energy Management","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3033556475","doi":"https://doi.org/10.1109/tvt.2020.2999263","mag":"3033556475"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2020.2999263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.2999263","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5036919166","display_name":"Renzong Lian","orcid":"https://orcid.org/0000-0001-9804-6370"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renzong Lian","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9804-6370","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085784813","display_name":"Huachun Tan","orcid":"https://orcid.org/0000-0001-6881-0550"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huachun Tan","raw_affiliation_strings":["School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079942913","display_name":"Jiankun Peng","orcid":"https://orcid.org/0000-0003-1444-9741"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiankun Peng","raw_affiliation_strings":["School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100438912","display_name":"Qin Li","orcid":"https://orcid.org/0000-0002-5789-2578"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qin Li","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100370856","display_name":"Yuankai Wu","orcid":"https://orcid.org/0000-0003-4435-9413"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Yuankai Wu","raw_affiliation_strings":["Department of Civil Engineering and Applied Mechanics, McGill University Montr\u00e9al, Canada","School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4435-9413","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering and Applied Mechanics, McGill University Montr\u00e9al, Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.3525,"has_fulltext":false,"cited_by_count":161,"citation_normalized_percentile":{"value":0.98139252,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"69","issue":"8","first_page":"8367","last_page":"8380"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9991000294685364,"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/electric-vehicle","display_name":"Electric vehicle","score":0.6656464338302612},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6126793026924133},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5914628505706787},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.5621023178100586},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5480114221572876},{"id":"https://openalex.org/keywords/energy-management","display_name":"Energy management","score":0.5313863158226013},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.5231783986091614},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5046461820602417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4787803888320923},{"id":"https://openalex.org/keywords/maximum-power-transfer-theorem","display_name":"Maximum power transfer theorem","score":0.4786480665206909},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46870702505111694},{"id":"https://openalex.org/keywords/knowledge-transfer","display_name":"Knowledge transfer","score":0.45585381984710693},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.4437541365623474},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4258759319782257},{"id":"https://openalex.org/keywords/hybrid-vehicle","display_name":"Hybrid vehicle","score":0.4173721373081207},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4108904004096985},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.3747332692146301},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.3476469814777374},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3429316282272339},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1730121374130249},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07813283801078796}],"concepts":[{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.6656464338302612},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6126793026924133},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5914628505706787},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.5621023178100586},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5480114221572876},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.5313863158226013},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.5231783986091614},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5046461820602417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4787803888320923},{"id":"https://openalex.org/C67186554","wikidata":"https://www.wikidata.org/wiki/Q17103352","display_name":"Maximum power transfer theorem","level":3,"score":0.4786480665206909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46870702505111694},{"id":"https://openalex.org/C2776960227","wikidata":"https://www.wikidata.org/wiki/Q2586354","display_name":"Knowledge transfer","level":2,"score":0.45585381984710693},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4437541365623474},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4258759319782257},{"id":"https://openalex.org/C516807790","wikidata":"https://www.wikidata.org/wiki/Q193075","display_name":"Hybrid vehicle","level":3,"score":0.4173721373081207},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4108904004096985},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3747332692146301},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3476469814777374},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3429316282272339},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1730121374130249},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07813283801078796},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2020.2999263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.2999263","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1938823714","display_name":null,"funder_award_id":"61620106002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2070015541","display_name":null,"funder_award_id":"51705020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W158722652","https://openalex.org/W1555307114","https://openalex.org/W1757796397","https://openalex.org/W2004919646","https://openalex.org/W2022997841","https://openalex.org/W2097381042","https://openalex.org/W2108720292","https://openalex.org/W2110442347","https://openalex.org/W2124085945","https://openalex.org/W2133597699","https://openalex.org/W2140635424","https://openalex.org/W2140833774","https://openalex.org/W2149933564","https://openalex.org/W2161381512","https://openalex.org/W2165698076","https://openalex.org/W2173248099","https://openalex.org/W2174786457","https://openalex.org/W2190859449","https://openalex.org/W2215010794","https://openalex.org/W2236204240","https://openalex.org/W2298052098","https://openalex.org/W2395579298","https://openalex.org/W2466636338","https://openalex.org/W2501655773","https://openalex.org/W2566257935","https://openalex.org/W2591714971","https://openalex.org/W2739678353","https://openalex.org/W2747402019","https://openalex.org/W2754517384","https://openalex.org/W2789725222","https://openalex.org/W2801441281","https://openalex.org/W2887280559","https://openalex.org/W2889970038","https://openalex.org/W2919115771","https://openalex.org/W2935913115","https://openalex.org/W2936616423","https://openalex.org/W2941560784","https://openalex.org/W2945493933","https://openalex.org/W2947693385","https://openalex.org/W2951762469","https://openalex.org/W2955254859","https://openalex.org/W2963120839","https://openalex.org/W2963864421","https://openalex.org/W2964352247","https://openalex.org/W2967987061","https://openalex.org/W2985293964","https://openalex.org/W3009193590","https://openalex.org/W3100789280","https://openalex.org/W4229515943","https://openalex.org/W4298174377","https://openalex.org/W4298857966","https://openalex.org/W4299518610","https://openalex.org/W6633178580","https://openalex.org/W6637967152","https://openalex.org/W6674600207","https://openalex.org/W6680887930","https://openalex.org/W6682132143","https://openalex.org/W6684921986","https://openalex.org/W6685726866","https://openalex.org/W6688449968","https://openalex.org/W6722524744","https://openalex.org/W6742945991","https://openalex.org/W6744123322","https://openalex.org/W6754782557"],"related_works":["https://openalex.org/W2005381771","https://openalex.org/W4365143455","https://openalex.org/W1132073915","https://openalex.org/W2032308896","https://openalex.org/W2551097806","https://openalex.org/W2392130781","https://openalex.org/W2066808393","https://openalex.org/W2980893407","https://openalex.org/W2164676366","https://openalex.org/W2548144399"],"abstract_inverted_index":{"Developing":[0],"energy":[1,108],"management":[2,109],"strategies":[3],"(EMSs)":[4],"for":[5,19,93,153,196],"different":[6,34,76,132,185],"types":[7,35,77],"of":[8,36,44,78,98,107,116,130,164],"hybrid":[9],"electric":[10],"vehicles":[11],"(HEVs)":[12],"is":[13,80,110,189],"a":[14,52,90,117,120,124,138],"time-consuming":[15],"and":[16,123],"laborious":[17],"task":[18],"automotive":[20],"engineers.":[21],"Experienced":[22],"engineers":[23],"can":[24,176],"reduce":[25],"the":[26,31,42,59,96,104,128,160,193],"developing":[27],"cycle":[28],"by":[29,145],"exploiting":[30],"commonalities":[32],"between":[33,63,179],"HEV":[37,45,133,197],"EMSs.":[38,69],"Aiming":[39],"at":[40],"improving":[41],"efficiency":[43,166],"EMSs":[46,115,134],"development":[47,194],"automatically,":[48],"this":[49],"paper":[50],"proposes":[51],"transfer":[53,62,72,147,177],"learning":[54,66,148],"based":[55,68],"method":[56],"to":[57,88,191],"achieve":[58],"cross-type":[60],"knowledge":[61,71,106,178],"deep":[64,100],"reinforcement":[65],"(DRL)":[67],"Specifically,":[70],"among":[73],"four":[74],"significantly":[75,184],"HEVs":[79,181],"studied.":[81],"We":[82],"first":[83],"use":[84],"massive":[85],"driving":[86],"cycles":[87],"train":[89],"DRL-based":[91,151],"EMS":[92,152],"Prius.":[94],"Then":[95],"parameters":[97,129],"its":[99],"neural":[101],"networks,":[102],"wherein":[103],"common":[105],"captured,":[111],"are":[112,135],"transferred":[113],"into":[114,150],"power-split":[118],"bus,":[119],"series":[121],"vehicle":[122],"series-parallel":[125],"bus.":[126],"Finally,":[127],"3":[131],"fine-tuned":[136],"in":[137,162],"small":[139],"dataset.":[140],"Simulation":[141],"results":[142],"indicate":[143],"that,":[144],"incorporating":[146],"(TL)":[149],"HEVs,":[154],"an":[155],"average":[156],"70%":[157],"gap":[158],"from":[159],"baseline":[161],"respect":[163],"convergence":[165],"has":[167],"been":[168],"achieved.":[169],"Our":[170],"study":[171],"also":[172],"shows":[173],"that":[174,182],"TL":[175,188],"two":[180],"have":[183],"structures.":[186],"Overall,":[187],"conducive":[190],"boost":[192],"process":[195],"EMS.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":15},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":38},{"year":2022,"cited_by_count":32},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":2}],"updated_date":"2026-08-08T07:41:36.138363","created_date":"2025-10-10T00:00:00"}
