{"id":"https://openalex.org/W2963167981","doi":"https://doi.org/10.1109/access.2019.2930680","title":"State of Health Estimation for Lithium-ion Batteries Based on Fusion of Autoregressive Moving Average Model and Elman Neural Network","display_name":"State of Health Estimation for Lithium-ion Batteries Based on Fusion of Autoregressive Moving Average Model and Elman Neural Network","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2963167981","doi":"https://doi.org/10.1109/access.2019.2930680","mag":"2963167981"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2930680","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2930680","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2019.2930680","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100750920","display_name":"Zheng Chen","orcid":"https://orcid.org/0000-0002-1634-7231"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Chen","raw_affiliation_strings":["Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":"https://orcid.org/0000-0002-1634-7231","affiliations":[{"raw_affiliation_string":"Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033736444","display_name":"Qiao Xue","orcid":"https://orcid.org/0000-0002-9916-6750"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiao Xue","raw_affiliation_strings":["Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011244486","display_name":"Renxin Xiao","orcid":"https://orcid.org/0000-0003-4394-3765"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renxin Xiao","raw_affiliation_strings":["Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111765470","display_name":"Yonggang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonggang Liu","raw_affiliation_strings":["State Key Laboratory of Mechanical Transmissions, School of Automotive Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-5814-104X","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mechanical Transmissions, School of Automotive Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025904667","display_name":"Jiangwei Shen","orcid":"https://orcid.org/0000-0003-1853-0782"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangwei Shen","raw_affiliation_strings":["Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.2051,"has_fulltext":false,"cited_by_count":121,"citation_normalized_percentile":{"value":0.96706162,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"102662","last_page":"102678"},"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":0.9936000108718872,"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/autoregressive-model","display_name":"Autoregressive model","score":0.6738278865814209},{"id":"https://openalex.org/keywords/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.6385313272476196},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6190474033355713},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6110381484031677},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.5465096235275269},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.49306103587150574},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.48982879519462585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47073471546173096},{"id":"https://openalex.org/keywords/grey-relational-analysis","display_name":"Grey relational analysis","score":0.46184319257736206},{"id":"https://openalex.org/keywords/lithium-ion-battery","display_name":"Lithium-ion battery","score":0.4570084512233734},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.41714534163475037},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35457122325897217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2904481887817383},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16538935899734497},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14701032638549805},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.09155350923538208}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6738278865814209},{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.6385313272476196},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6190474033355713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6110381484031677},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.5465096235275269},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.49306103587150574},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.48982879519462585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47073471546173096},{"id":"https://openalex.org/C64734493","wikidata":"https://www.wikidata.org/wiki/Q5608296","display_name":"Grey relational analysis","level":2,"score":0.46184319257736206},{"id":"https://openalex.org/C2779197387","wikidata":"https://www.wikidata.org/wiki/Q2822895","display_name":"Lithium-ion battery","level":4,"score":0.4570084512233734},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.41714534163475037},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35457122325897217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2904481887817383},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16538935899734497},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14701032638549805},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.09155350923538208},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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":3,"locations":[{"id":"doi:10.1109/access.2019.2930680","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2930680","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6a83314eae114d459b767d8b0fdb04b5","is_oa":true,"landing_page_url":"https://doaj.org/article/6a83314eae114d459b767d8b0fdb04b5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 102662-102678 (2019)","raw_type":"article"},{"id":"pmh:oai:zenodo.org:5457666","is_oa":true,"landing_page_url":"https://zenodo.org/record/5457666","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2930680","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2930680","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1675492613","display_name":null,"funder_award_id":"845102-HOEMEV-H2020-MSCAIF-2018","funder_id":"https://openalex.org/F4320338337","funder_display_name":"H2020 Marie Sk\u0142odowska-Curie Actions"},{"id":"https://openalex.org/G7749486762","display_name":null,"funder_award_id":"51775063","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8385415527","display_name":null,"funder_award_id":"61763021","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8816691621","display_name":null,"funder_award_id":"2018YFB0104500","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320338337","display_name":"H2020 Marie Sk\u0142odowska-Curie Actions","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1185746543","https://openalex.org/W1515988900","https://openalex.org/W1693496066","https://openalex.org/W1966039250","https://openalex.org/W1982949309","https://openalex.org/W1985272283","https://openalex.org/W2004193933","https://openalex.org/W2007221293","https://openalex.org/W2017136542","https://openalex.org/W2047152377","https://openalex.org/W2083936599","https://openalex.org/W2088378662","https://openalex.org/W2122917607","https://openalex.org/W2129276500","https://openalex.org/W2160656970","https://openalex.org/W2272128138","https://openalex.org/W2406444459","https://openalex.org/W2412442442","https://openalex.org/W2413008292","https://openalex.org/W2434605170","https://openalex.org/W2497266549","https://openalex.org/W2500303754","https://openalex.org/W2501990625","https://openalex.org/W2525355983","https://openalex.org/W2561686939","https://openalex.org/W2621249114","https://openalex.org/W2729150869","https://openalex.org/W2734898034","https://openalex.org/W2762736364","https://openalex.org/W2767663538","https://openalex.org/W2774992281","https://openalex.org/W2783030034","https://openalex.org/W2793702125","https://openalex.org/W2794433444","https://openalex.org/W2794605228","https://openalex.org/W2805870878","https://openalex.org/W2810093868","https://openalex.org/W2890169947","https://openalex.org/W2895147187","https://openalex.org/W2896294159","https://openalex.org/W2899724047","https://openalex.org/W2899792027","https://openalex.org/W2902107055","https://openalex.org/W2903897327","https://openalex.org/W2904504253","https://openalex.org/W2910616588","https://openalex.org/W2910741532","https://openalex.org/W2921358399","https://openalex.org/W2924382816","https://openalex.org/W3098332525"],"related_works":["https://openalex.org/W3014107421","https://openalex.org/W2363056446","https://openalex.org/W2081563414","https://openalex.org/W2359718298","https://openalex.org/W2377062149","https://openalex.org/W2380939102","https://openalex.org/W154554909","https://openalex.org/W2072581623","https://openalex.org/W3115491726","https://openalex.org/W3190289737"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3],"fusion":[4,159],"model":[5,13,118,122],"based":[6],"on":[7],"the":[8,24,33,40,45,50,55,62,65,69,78,84,97,103,116,128,138,145,157,162,170],"autoregressive":[9],"moving":[10],"average":[11],"(ARMA)":[12],"and":[14,35,49,82,90,110,119,133,174],"Elman":[15,120,175],"neural":[16],"network":[17],"(NN)":[18],"to":[19,54,61,76,143,154],"achieve":[20],"accurate":[21],"prediction":[22,164],"for":[23],"state":[25],"of":[26,29,39,64,86],"health":[27,51,111],"(SOH)":[28],"lithium-ion":[30],"batteries.":[31],"First,":[32],"voltage":[34,66],"capacity":[36,79,88],"degradation":[37,80],"variation":[38,63],"battery":[41,46,56],"are":[42,100,113,123,141],"acquired":[43],"through":[44],"lifecycle":[47],"data,":[48],"factor":[52,112],"related":[53,98],"aging":[57],"is":[58,74,152],"selected":[59],"according":[60],"profile.":[67],"Second,":[68],"empirical":[70],"mode":[71],"decomposition":[72],"(EMD)":[73],"employed":[75],"process":[77],"data":[81,92,132],"eliminate":[83],"phenomenon":[85],"tiny":[87],"recovery,":[89],"multiple":[91],"sequences,":[93],"as":[94,96],"well":[95],"residue,":[99],"extracted,":[101],"then":[102],"grey":[104],"relational":[105],"analysis":[106],"(GRA)":[107],"between":[108],"sub-sequences":[109],"discussed.":[114],"Furthermore,":[115],"ARMA":[117,172],"NN":[121,176],"respectively":[124],"built":[125],"by":[126],"training":[127],"subsequent":[129],"time":[130],"series":[131],"residue":[134],"data.":[135],"Finally,":[136],"all":[137],"individual":[139],"predictions":[140],"combined":[142],"generate":[144],"estimated":[146],"SOH":[147,163],"sequences.":[148],"The":[149],"experimental":[150],"validation":[151],"performed":[153],"manifest":[155],"that":[156],"addressed":[158],"method":[160,173],"performs":[161],"with":[165,169],"satisfactory":[166],"accuracy,":[167],"compared":[168],"single":[171],"model.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":29},{"year":2020,"cited_by_count":15}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
