{"id":"https://openalex.org/W4412486957","doi":"https://doi.org/10.1109/tencon61640.2024.10902858","title":"Battery SOH Estimation Using LSTM with Genetic Algorithm-Based Hyperparameter Optimization","display_name":"Battery SOH Estimation Using LSTM with Genetic Algorithm-Based Hyperparameter Optimization","publication_year":2024,"publication_date":"2024-12-01","ids":{"openalex":"https://openalex.org/W4412486957","doi":"https://doi.org/10.1109/tencon61640.2024.10902858"},"language":"en","primary_location":{"id":"doi:10.1109/tencon61640.2024.10902858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon61640.2024.10902858","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON)","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/A5086032740","display_name":"K. Ponnambalam","orcid":"https://orcid.org/0000-0002-4107-4829"},"institutions":[{"id":"https://openalex.org/I4210094553","display_name":"Newcastle University Singapore","ror":"https://ror.org/00mbfhq81","country_code":"SG","type":"education","lineage":["https://openalex.org/I4210094553"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Karthickumar Ponnambalam","raw_affiliation_strings":["Newcastle University,Singapore"],"affiliations":[{"raw_affiliation_string":"Newcastle University,Singapore","institution_ids":["https://openalex.org/I4210094553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111936402","display_name":"B. Sivaneasan","orcid":null},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"B. Sivaneasan","raw_affiliation_strings":["Singapore Institute of Technology,Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology,Singapore","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003778851","display_name":"Arvind Sharma","orcid":"https://orcid.org/0000-0001-5526-858X"},"institutions":[{"id":"https://openalex.org/I4210094553","display_name":"Newcastle University Singapore","ror":"https://ror.org/00mbfhq81","country_code":"SG","type":"education","lineage":["https://openalex.org/I4210094553"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"A. Sharma","raw_affiliation_strings":["Newcastle University,Singapore"],"affiliations":[{"raw_affiliation_string":"Newcastle University,Singapore","institution_ids":["https://openalex.org/I4210094553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028528453","display_name":"S. S. Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094553","display_name":"Newcastle University Singapore","ror":"https://ror.org/00mbfhq81","country_code":"SG","type":"education","lineage":["https://openalex.org/I4210094553"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"S. S. Lee","raw_affiliation_strings":["Newcastle University,Singapore"],"affiliations":[{"raw_affiliation_string":"Newcastle University,Singapore","institution_ids":["https://openalex.org/I4210094553"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089771051","display_name":"Pr\u0105sun Chakrabarti","orcid":"https://orcid.org/0000-0001-8062-4144"},"institutions":[{"id":"https://openalex.org/I94511900","display_name":"Sir Padampat Singhania University","ror":"https://ror.org/03mhsvf98","country_code":"IN","type":"education","lineage":["https://openalex.org/I94511900"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Prasun Chakrabarti","raw_affiliation_strings":["Sir Padampat Singhania University,India"],"affiliations":[{"raw_affiliation_string":"Sir Padampat Singhania University,India","institution_ids":["https://openalex.org/I94511900"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5086032740"],"corresponding_institution_ids":["https://openalex.org/I4210094553"],"apc_list":null,"apc_paid":null,"fwci":0.2162,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.559724,"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":"1632","last_page":"1635"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9469000101089478,"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/T12941","display_name":"Embedded Systems and FPGA Design","score":0.9154000282287598,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/hyperparameter","display_name":"Hyperparameter","score":0.873741626739502},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6614322662353516},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5219804048538208},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.476840615272522},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4743441641330719},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4721275269985199},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.46938154101371765},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42242133617401123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41294023394584656},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.24326005578041077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1192743182182312},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10512283444404602}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.873741626739502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6614322662353516},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5219804048538208},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.476840615272522},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4743441641330719},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4721275269985199},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.46938154101371765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42242133617401123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41294023394584656},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.24326005578041077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1192743182182312},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10512283444404602},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"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/tencon61640.2024.10902858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon61640.2024.10902858","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1971259134","https://openalex.org/W2000702553","https://openalex.org/W2055873761","https://openalex.org/W2074017120","https://openalex.org/W2108793665","https://openalex.org/W2548869838","https://openalex.org/W2791939925","https://openalex.org/W2895397433","https://openalex.org/W2955134049","https://openalex.org/W2985862567","https://openalex.org/W3096106062","https://openalex.org/W3110175444","https://openalex.org/W3118751056","https://openalex.org/W3142230727","https://openalex.org/W3210605446","https://openalex.org/W3217683824","https://openalex.org/W4220987302","https://openalex.org/W4313382533","https://openalex.org/W4381663952","https://openalex.org/W4381884115"],"related_works":["https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W2140186469","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W2775233965","https://openalex.org/W4318559728","https://openalex.org/W4360995913","https://openalex.org/W4312193868","https://openalex.org/W2382364780"],"abstract_inverted_index":{"The":[0,90,111,141,188],"effective":[1],"operation":[2],"and":[3,73,109,123,138],"management":[4],"of":[5,14,34,37,157,201],"battery-based":[6],"energy":[7],"storage":[8],"devices":[9],"hinge":[10],"upon":[11],"timely":[12],"assessment":[13],"battery":[15,42,155,223],"health.":[16],"This":[17,205],"paper":[18],"introduces":[19,102],"an":[20,86],"optimized":[21,113,147],"deep":[22],"learning":[23],"approach":[24],"utilizing":[25],"Artificial":[26],"Neural":[27],"Networks":[28],"(ANN)":[29],"for":[30,53,75,105,222],"assessing":[31],"the":[32,97,119,145,174],"State":[33,156],"Health":[35,158],"(SoH)":[36,159],"lithium-ion":[38],"batteries,":[39],"leveraging":[40],"on":[41,71],"aging":[43],"datasets":[44],"from":[45,193],"NASA's":[46],"Open":[47],"Data":[48],"Portal.":[49],"An":[50],"innovative":[51],"methodology":[52,93],"optimizing":[54],"Long":[55],"Short-Term":[56],"Memory":[57],"(LSTM)":[58],"hyperparameters":[59],"using":[60,118],"Genetic":[61],"Algorithm":[62],"(GA)":[63],"is":[64,116],"also":[65,101],"proposed.":[66],"Traditional":[67],"approaches":[68],"rely":[69],"heavily":[70],"trial":[72],"error":[74],"hyperparameter":[76],"determination,":[77],"facing":[78],"challenges":[79],"in":[80,153,185,190],"selecting":[81],"optimal":[82],"parameters":[83,130],"due":[84],"to":[85,173,195],"expansive":[87],"search":[88],"space.":[89],"proposed":[91,146],"systematic":[92],"not":[94],"only":[95],"identifies":[96],"best":[98],"architecture":[99],"but":[100],"novel":[103,112],"criteria":[104],"evaluating":[106],"ANN":[107],"performance":[108,152],"complexity.":[110],"GA-LSTM":[114,148],"model":[115,149,221],"trained":[117,198],"curated":[120],"NASA":[121],"data,":[122],"its":[124,129,214],"accuracy":[125],"evaluated":[126],"by":[127],"fine-tuning":[128],"such":[131],"as":[132,216],"batch":[133],"size,":[134,136],"unit":[135],"activation":[137],"loss":[139],"functions.":[140],"results":[142],"demonstrate":[143],"that":[144],"exhibits":[150],"better":[151],"estimating":[154],"across":[160],"diverse":[161],"conditions,":[162],"achieving":[163],"significantly":[164],"improved":[165],"Root":[166],"Mean":[167],"Square":[168],"Error":[169],"(RMSE)":[170],"values":[171],"compared":[172],"Particle":[175],"Swarm":[176],"Optimization":[177],"algorithm":[178],"aided":[179],"LSTM":[180],"model,":[181],"namely":[182],"PA-LSTM,":[183],"introduced":[184],"recent":[186],"research.":[187],"improvement":[189],"RMSE":[191],"ranges":[192],"12.4%":[194],"76.79%":[196],"when":[197],"with":[199],"70%":[200],"discharge":[202],"cycle":[203],"data.":[204],"represents":[206],"a":[207,217],"notable":[208],"enhancement":[209],"over":[210],"previous":[211],"methods,":[212],"highlighting":[213],"efficacy":[215],"more":[218],"accurate":[219],"prediction":[220],"health":[224],"assessment.":[225]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}