{"id":"https://openalex.org/W3048493514","doi":"https://doi.org/10.1109/tii.2020.3015748","title":"Hybrid Electric Vehicle Energy Management With Computer Vision and Deep Reinforcement Learning","display_name":"Hybrid Electric Vehicle Energy Management With Computer Vision and Deep Reinforcement Learning","publication_year":2020,"publication_date":"2020-08-11","ids":{"openalex":"https://openalex.org/W3048493514","doi":"https://doi.org/10.1109/tii.2020.3015748","mag":"3048493514"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2020.3015748","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2020.3015748","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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/A5100424464","display_name":"Yong Wang","orcid":"https://orcid.org/0000-0002-6063-5767"},"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":true,"raw_author_name":"Yong Wang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"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":["Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuankai Wu","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","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":["Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100424464"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":7.0732,"has_fulltext":false,"cited_by_count":139,"citation_normalized_percentile":{"value":0.97749927,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"17","issue":"6","first_page":"3857","last_page":"3868"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9990000128746033,"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":0.9976000189781189,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.803402841091156},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6648149490356445},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.556818962097168},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5285826325416565},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4960728585720062},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45595812797546387},{"id":"https://openalex.org/keywords/energy-management","display_name":"Energy management","score":0.4497338831424713},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.447163462638855},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.44376662373542786},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.3353731632232666},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2559893727302551},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.1378045678138733}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.803402841091156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6648149490356445},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.556818962097168},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5285826325416565},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4960728585720062},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45595812797546387},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.4497338831424713},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.447163462638855},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.44376662373542786},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3353731632232666},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2559893727302551},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.1378045678138733},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2020.3015748","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2020.3015748","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"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"},{"id":"https://openalex.org/G6604592933","display_name":null,"funder_award_id":"2242020R10045","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1555307114","https://openalex.org/W1991725038","https://openalex.org/W2067418529","https://openalex.org/W2089988774","https://openalex.org/W2148881573","https://openalex.org/W2165150801","https://openalex.org/W2173248099","https://openalex.org/W2466636338","https://openalex.org/W2483814582","https://openalex.org/W2515170416","https://openalex.org/W2548722511","https://openalex.org/W2561145466","https://openalex.org/W2619984247","https://openalex.org/W2623491082","https://openalex.org/W2766979576","https://openalex.org/W2790928508","https://openalex.org/W2796096089","https://openalex.org/W2796347433","https://openalex.org/W2801441281","https://openalex.org/W2901472231","https://openalex.org/W2908896109","https://openalex.org/W2922677020","https://openalex.org/W2936616423","https://openalex.org/W2941560784","https://openalex.org/W2945021260","https://openalex.org/W2945493933","https://openalex.org/W2954811524","https://openalex.org/W2955254859","https://openalex.org/W3040318838","https://openalex.org/W4214717370","https://openalex.org/W4302570325","https://openalex.org/W6633178580","https://openalex.org/W6684205842"],"related_works":["https://openalex.org/W4382644535","https://openalex.org/W2522768275","https://openalex.org/W2352938035","https://openalex.org/W2351672553","https://openalex.org/W2373392303","https://openalex.org/W4362501864","https://openalex.org/W4306904969","https://openalex.org/W2765894405","https://openalex.org/W2061181932","https://openalex.org/W2969228573"],"abstract_inverted_index":{"Modern":[0],"automotive":[1],"systems":[2],"have":[3],"been":[4],"equipped":[5],"with":[6,127,135],"a":[7,86,90],"highly":[8],"increasing":[9],"number":[10],"of":[11,42,51,149],"onboard":[12,77],"computer":[13,30],"vision":[14,31],"hardware":[15],"and":[16,32,110,141],"software,":[17],"which":[18,115],"are":[19],"considered":[20],"to":[21,37,71,94],"be":[22],"beneficial":[23],"for":[24,89],"achieving":[25],"eco-driving.":[26],"This":[27],"article":[28],"combines":[29],"deep":[33],"reinforcement":[34],"learning":[35,53],"(DRL)":[36],"improve":[38],"the":[39,54,101,124,136,142,150],"fuel":[40,133,147],"economy":[41,148],"hybrid":[43],"electric":[44],"vehicles.":[45],"The":[46,61,79,120],"proposed":[47,102,143],"method":[48,68,144],"is":[49,69,83,118],"capable":[50],"autonomously":[52],"optimal":[55],"control":[56],"policy":[57],"from":[58,76],"visual":[59,74,81,116,128,139],"inputs.":[60],"state-of-the-art":[62],"convolutional":[63],"neural":[64],"networks-based":[65],"object":[66],"detection":[67],"utilized":[70],"extract":[72],"available":[73],"information":[75,82,117,129],"cameras.":[78],"detected":[80],"used":[84],"as":[85],"state":[87],"input":[88],"continuous":[91],"DRL":[92],"model":[93],"output":[95],"energy":[96],"management":[97],"strategies.":[98],"To":[99],"evaluate":[100],"method,":[103],"we":[104],"construct":[105],"100":[106],"km":[107],"real":[108],"city":[109],"highway":[111],"driving":[112],"cycles,":[113],"in":[114],"incorporated.":[119],"results":[121],"show":[122],"that":[123],"DRL-based":[125],"system":[126],"consumes":[130],"4.3-8.8%":[131],"less":[132],"compared":[134],"one":[137],"without":[138],"information,":[140],"achieves":[145],"96.5%":[146],"global":[151],"optimum-dynamic":[152],"programming.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":26},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}
