{"id":"https://openalex.org/W4315472436","doi":"https://doi.org/10.1109/mesa55290.2022.10004390","title":"Fractional Order Backpropagation Neural Network for Battery Capacity Estimation with Realistic Vehicle Data","display_name":"Fractional Order Backpropagation Neural Network for Battery Capacity Estimation with Realistic Vehicle Data","publication_year":2022,"publication_date":"2022-11-28","ids":{"openalex":"https://openalex.org/W4315472436","doi":"https://doi.org/10.1109/mesa55290.2022.10004390"},"language":"en","primary_location":{"id":"doi:10.1109/mesa55290.2022.10004390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mesa55290.2022.10004390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 18th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","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/A5100385397","display_name":"Yanan Wang","orcid":"https://orcid.org/0000-0003-0445-1696"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanan Wang","raw_affiliation_strings":["School of Vehicle and mobility, Tsinghua University,Beijing,China,100084"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and mobility, Tsinghua University,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100611797","display_name":"Xuebing Han","orcid":"https://orcid.org/0000-0001-7896-9354"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuebing Han","raw_affiliation_strings":["School of Vehicle and mobility, Tsinghua University,Beijing,China,100084"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and mobility, Tsinghua University,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102922185","display_name":"Feng Dai","orcid":"https://orcid.org/0000-0003-3197-5487"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng Dai","raw_affiliation_strings":["Sichuan New Energy Vehicle, Innovation Center Co. Ltd.,Yibin,China,644000"],"affiliations":[{"raw_affiliation_string":"Sichuan New Energy Vehicle, Innovation Center Co. Ltd.,Yibin,China,644000","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100428316","display_name":"Jie Li","orcid":"https://orcid.org/0000-0003-0478-8539"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jie Li","raw_affiliation_strings":["Sichuan New Energy Vehicle, Innovation Center Co. Ltd.,Yibin,China,644000"],"affiliations":[{"raw_affiliation_string":"Sichuan New Energy Vehicle, Innovation Center Co. Ltd.,Yibin,China,644000","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061434865","display_name":"Daijiang Zou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daijiang Zou","raw_affiliation_strings":["Sichuan New Energy Vehicle, Innovation Center Co. Ltd.,Yibin,China,644000"],"affiliations":[{"raw_affiliation_string":"Sichuan New Energy Vehicle, Innovation Center Co. Ltd.,Yibin,China,644000","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083736034","display_name":"Languang Lu","orcid":"https://orcid.org/0000-0002-2033-3430"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Languang Lu","raw_affiliation_strings":["School of Vehicle and mobility, Tsinghua University,Beijing,China,100084"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and mobility, Tsinghua University,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100715957","display_name":"YangQuan Chen","orcid":"https://orcid.org/0000-0002-7422-5988"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yangquan Chen","raw_affiliation_strings":["University of California,Department of Engineering,Merced,CA,USA,95343"],"affiliations":[{"raw_affiliation_string":"University of California,Department of Engineering,Merced,CA,USA,95343","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101407209","display_name":"Minggao Ouyang","orcid":"https://orcid.org/0000-0002-9142-8488"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minggao Ouyang","raw_affiliation_strings":["School of Vehicle and mobility, Tsinghua University,Beijing,China,100084"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and mobility, Tsinghua University,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100385397"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0775,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.38701794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"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/T10663","display_name":"Advanced Battery Technologies Research","score":1.0,"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":1.0,"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/T10018","display_name":"Advancements in Battery Materials","score":0.9927999973297119,"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":0.9926999807357788,"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/backpropagation","display_name":"Backpropagation","score":0.8757292032241821},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7111935615539551},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6261614561080933},{"id":"https://openalex.org/keywords/battery-capacity","display_name":"Battery capacity","score":0.5874412059783936},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.475433349609375},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.4465025067329407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37576061487197876},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17819306254386902},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.09922745823860168}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8757292032241821},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7111935615539551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6261614561080933},{"id":"https://openalex.org/C2989104859","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery capacity","level":4,"score":0.5874412059783936},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.475433349609375},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.4465025067329407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37576061487197876},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17819306254386902},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.09922745823860168},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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},{"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/mesa55290.2022.10004390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mesa55290.2022.10004390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 18th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G3589887796","display_name":null,"funder_award_id":"3212031","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G5760517129","display_name":null,"funder_award_id":"62103220,52177217","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"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2347014962","https://openalex.org/W2922751030","https://openalex.org/W2924382816","https://openalex.org/W2967681467","https://openalex.org/W2972468192","https://openalex.org/W2979169247","https://openalex.org/W2994341517","https://openalex.org/W3003911265","https://openalex.org/W3027239763","https://openalex.org/W3097439325","https://openalex.org/W3106603010","https://openalex.org/W3108279751","https://openalex.org/W3119174963","https://openalex.org/W3126452185","https://openalex.org/W3167452794","https://openalex.org/W3182713161","https://openalex.org/W4200390501","https://openalex.org/W4224947065"],"related_works":["https://openalex.org/W2894173309","https://openalex.org/W4387932263","https://openalex.org/W2098962763","https://openalex.org/W2371065793","https://openalex.org/W2157746493","https://openalex.org/W4308964873","https://openalex.org/W2768611900","https://openalex.org/W2729780499","https://openalex.org/W2384016584","https://openalex.org/W2543699259"],"abstract_inverted_index":{"For":[0,134],"battery":[1,15,86,137,166,180,195],"capacity":[2,60,127,140,167,192],"estimation,":[3],"machine":[4],"learning":[5],"(ML)":[6],"algorithm":[7,21,152],"has":[8],"drawn":[9],"much":[10],"attention":[11],"in":[12,109],"the":[13,24,44,59,67,72,77,85,95,126,131,135,151,155,174,179,190],"intelligent":[14],"management":[16],"field.":[17],"The":[18,89,169],"state-of-art":[19],"ML":[20,65,74],"cannot":[22,37],"describe":[23],"inside":[25],"reactions":[26],"of":[27,46,80,114,130],"LIBs,":[28,81],"while":[29],"electrochemical":[30],"model":[31],"with":[32,76,161],"complicated":[33],"partial":[34],"differential":[35],"equations":[36],"be":[38],"deployed":[39],"to":[40,94,124,164],"realistic":[41,136],"applications.":[42],"On":[43],"basis":[45],"fractional-order":[47,53,69,73,78,90,101,157,175],"calculus,":[48],"this":[49,142],"paper":[50,143],"proposes":[51],"a":[52,100],"backpropagation":[54,110],"neural":[55],"network":[56],"(BPNN)":[57],"for":[58,106,150,189],"estimation.":[61],"As":[62],"an":[63],"enhanced":[64],"algorithm,":[66],"proposed":[68,132,156],"BPNN":[70,158,176],"combines":[71],"theory":[75],"modeling":[79],"which":[82],"can":[83,177],"reflect":[84],"diffusion":[87],"dynamics.":[88],"gradient":[91,96,102],"is":[92,159],"introduced":[93],"descent":[97,103],"method,":[98],"constructing":[99],"(FOGD)":[104],"method":[105,163],"weight":[107],"update":[108],"process.":[111],"A":[112],"set":[113],"17":[115],"electric":[116],"vehicles":[117],"(EVs)":[118],"data":[119,138],"are":[120],"collected":[121],"and":[122,146,183],"preprocessed":[123],"verify":[125],"estimation":[128,185],"effects":[129],"algorithm.":[133],"without":[139],"labels,":[141],"firstly":[144],"deduces":[145],"provides":[147],"\u201cpseudo\u201d":[148],"labels":[149],"training,":[153],"then":[154],"trained":[160],"FOGD":[162],"learn":[165,178],"changes.":[168],"experiment":[170],"results":[171],"show":[172],"that":[173],"degradation":[181],"trend":[182],"maintain":[184],"accuracy":[186],"within":[187],"4.5%":[188],"whole":[191],"curve":[193],"during":[194],"lifetime.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}