{"id":"https://openalex.org/W4390678240","doi":"https://doi.org/10.1109/icsrs59833.2023.10381196","title":"PNP-Lightweight Model for Predicting Remaining Useful Life of Lithium-Ion Battery to Applying Embedded Systems","display_name":"PNP-Lightweight Model for Predicting Remaining Useful Life of Lithium-Ion Battery to Applying Embedded Systems","publication_year":2023,"publication_date":"2023-11-22","ids":{"openalex":"https://openalex.org/W4390678240","doi":"https://doi.org/10.1109/icsrs59833.2023.10381196"},"language":"en","primary_location":{"id":"doi:10.1109/icsrs59833.2023.10381196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsrs59833.2023.10381196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 7th International Conference on System Reliability and Safety (ICSRS)","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/A5077560442","display_name":"Gwi-Man Bak","orcid":"https://orcid.org/0000-0003-1219-2751"},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Gwi-man Bak","raw_affiliation_strings":["Chonnam National University,Department of Electrical and Semiconductor,Yeosu,Korea","Department of Electrical and Semiconductor, Chonnam National University, Yeosu, Korea"],"affiliations":[{"raw_affiliation_string":"Chonnam National University,Department of Electrical and Semiconductor,Yeosu,Korea","institution_ids":["https://openalex.org/I111277659"]},{"raw_affiliation_string":"Department of Electrical and Semiconductor, Chonnam National University, Yeosu, Korea","institution_ids":["https://openalex.org/I111277659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082258064","display_name":"Eunseong Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eun-seo Lee","raw_affiliation_strings":["Chonnam National University,Department of Electrical and Semiconductor,Yeosu,Korea","Department of Electrical and Semiconductor, Chonnam National University, Yeosu, Korea"],"affiliations":[{"raw_affiliation_string":"Chonnam National University,Department of Electrical and Semiconductor,Yeosu,Korea","institution_ids":["https://openalex.org/I111277659"]},{"raw_affiliation_string":"Department of Electrical and Semiconductor, Chonnam National University, Yeosu, Korea","institution_ids":["https://openalex.org/I111277659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085351058","display_name":"Young-Chul Bae","orcid":"https://orcid.org/0000-0003-3184-9667"},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Young-chul Bae","raw_affiliation_strings":["Chonnam National University,Division of Electrical and Computer Engineering,Yeosu,Korea","Division of Electrical and Computer Engineering, Chonnam National University, Yeosu, Korea"],"affiliations":[{"raw_affiliation_string":"Chonnam National University,Division of Electrical and Computer Engineering,Yeosu,Korea","institution_ids":["https://openalex.org/I111277659"]},{"raw_affiliation_string":"Division of Electrical and Computer Engineering, Chonnam National University, Yeosu, Korea","institution_ids":["https://openalex.org/I111277659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077560442"],"corresponding_institution_ids":["https://openalex.org/I111277659"],"apc_list":null,"apc_paid":null,"fwci":0.1148,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44614676,"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":"53","last_page":"60"},"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":0.9925000071525574,"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/T12238","display_name":"Green IT and Sustainability","score":0.9678999781608582,"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/perceptron","display_name":"Perceptron","score":0.6723957657814026},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6615153551101685},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.6513069868087769},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6231412887573242},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5910542011260986},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.52527916431427},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4811207354068756},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.47761768102645874},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.451323926448822},{"id":"https://openalex.org/keywords/state-of-charge","display_name":"State of charge","score":0.4294929504394531},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4276408553123474},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3335553705692291},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.32059091329574585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13482585549354553},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10272163152694702}],"concepts":[{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6723957657814026},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6615153551101685},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.6513069868087769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6231412887573242},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5910542011260986},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.52527916431427},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4811207354068756},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.47761768102645874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.451323926448822},{"id":"https://openalex.org/C2776582896","wikidata":"https://www.wikidata.org/wiki/Q5368536","display_name":"State of charge","level":4,"score":0.4294929504394531},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4276408553123474},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3335553705692291},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.32059091329574585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13482585549354553},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10272163152694702},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsrs59833.2023.10381196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsrs59833.2023.10381196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 7th International Conference on System Reliability and Safety (ICSRS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4172328907","display_name":null,"funder_award_id":"2021RIS-002","funder_id":"https://openalex.org/F4320311649","funder_display_name":"Ministry of Education"}],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1949231392","https://openalex.org/W2006315568","https://openalex.org/W2127856528","https://openalex.org/W2155832827","https://openalex.org/W2180987904","https://openalex.org/W2312874713","https://openalex.org/W2769502706","https://openalex.org/W2796568833","https://openalex.org/W2804051352","https://openalex.org/W2924382816","https://openalex.org/W2941227905","https://openalex.org/W2981965255","https://openalex.org/W3030331576","https://openalex.org/W3049495830","https://openalex.org/W3080095839","https://openalex.org/W3122893890","https://openalex.org/W3127344709","https://openalex.org/W3136516786","https://openalex.org/W3169854270","https://openalex.org/W3216627126","https://openalex.org/W4224947065","https://openalex.org/W4318619660","https://openalex.org/W4320517130","https://openalex.org/W4322102109","https://openalex.org/W4376612884","https://openalex.org/W6631190155"],"related_works":["https://openalex.org/W1562159987","https://openalex.org/W2004734718","https://openalex.org/W3190332208","https://openalex.org/W4388623464","https://openalex.org/W3126531014","https://openalex.org/W2519883542","https://openalex.org/W2098124661","https://openalex.org/W3006423619","https://openalex.org/W4385625847","https://openalex.org/W3195056770"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,46,55,171,209],"Positive":[4],"&":[5],"Negative":[6],"Perceptron":[7],"(PNP)-Lightweight":[8],"model":[9,37,43,57,110,117,125],"prediction":[10,18],"method":[11],"for":[12,23],"the":[13,41,61,64,67,73,78,81,88,108,115,123,130,135,147,153,158,162,174,180,186,201,206,224,231,239,247,257],"Remaining":[14],"Useful":[15],"Life":[16],"(RUL)":[17],"of":[19,50,63,72,80,132,150,155,161,173,182,185,194,238,269],"Lithium-Ion":[20],"Battery":[21],"(LIB)":[22],"use":[24],"in":[25,157],"low":[26,48],"computation":[27],"environments":[28],"such":[29],"as":[30],"smartphones":[31],"and":[32,44,69,97,119,139,152,196,219,226,243,249,262],"embedded":[33],"systems.":[34],"The":[35],"PNP-Lightweight":[36,56,109],"is":[38,188,241,272],"based":[39],"on":[40],"PNP":[42],"has":[45,208],"very":[47],"number":[49,149,154,181],"trainable":[51,183],"parameters.":[52],"We":[53,103,203,265],"present":[54],"that":[58,127,179,193,205,267],"can":[59,128],"predict":[60,129],"RUL":[62,131],"LIB":[65,133],"using":[66,107,114,122,134],"charge":[68,138],"discharge":[70,140],"data":[71],"initial":[74,137],"LIB.":[75],"To":[76,142],"prove":[77],"superiority":[79],"proposed":[82,260,270],"PNP-":[83],"Lightweight":[84],"model,":[85],"we":[86,145,177,254],"perform":[87],"performance":[89,175,258,268],"evaluation":[90],"compared":[91,222],"with":[92],"Long":[93],"short-term":[94],"memory":[95],"(LSTM)":[96],"Convolution":[98],"Neural":[99],"Network":[100],"(CNN)":[101],"models.":[102],"build":[104],"Deep-learning":[105,112,120],"Model":[106,113,121],"(DMP),":[111],"LSTM":[116],"(DML)":[118],"CNN":[124],"(DMC)":[126],"LIB's":[136],"data.":[141],"evaluate":[143],"fairly,":[144],"organize":[146],"same":[148],"layers":[151],"nodes":[156],"hidden":[159],"layer":[160],"three":[163],"deep-learning":[164],"models":[165],"(DMP,":[166],"DML,":[167],"and,":[168],"DMC)":[169],"As":[170],"result":[172],"evaluation,":[176],"know":[178],"parameters":[184],"DMP":[187,207,240,261,271],"30":[189],"times":[190,198],"lower":[191,199,210,245],"than":[192,200,246],"DML":[195,225,248],"60":[197],"DMC.":[202],"confirm":[204],"Root":[211],"Mean":[212,233],"Square":[213],"Error":[214,236],"(RMSE)":[215],"by":[216],"16.18":[217],"[cycle]":[218,221],"3.03":[220],"to":[223,274],"DMC,":[227,250],"respectively.":[228,251],"In":[229,252],"addition,":[230,253],"Symmetric":[232],"Absolute":[234],"Percentage":[235],"(SMAPE)":[237],"3.6%":[242],"3.96%":[244],"also":[255],"compare":[256],"between":[259],"CNN+LSTM":[263,275],"model.":[264,276],"recognize":[266],"superior":[273]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
