{"id":"https://openalex.org/W7204759771","doi":"https://doi.org/10.1016/j.est.2026.124158","title":"Battery prognostics using single-cycle statistical inference and parametric discharge curves","display_name":"Battery prognostics using single-cycle statistical inference and parametric discharge curves","publication_year":2026,"publication_date":"2026-08-31","ids":{"openalex":"https://openalex.org/W7204759771","doi":"https://doi.org/10.1016/j.est.2026.124158"},"language":"en","primary_location":{"id":"doi:10.1016/j.est.2026.124158","doi":"https://doi.org/10.1016/j.est.2026.124158","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.est.2026.124158","pdf_url":null,"source":{"id":"https://openalex.org/S2764865925","display_name":"Journal of Energy Storage","issn_l":"2352-152X","issn":["2352-152X","2352-1538"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-2","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Energy Storage","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.est.2026.124158","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081349580","display_name":"Anas Karaki","orcid":"https://orcid.org/0000-0003-4302-9367","observed_orcids":["https://orcid.org/0000-0003-4302-9367"]},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":true,"raw_author_name":"Anas Karaki","raw_affiliation_strings":["College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar","Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0003-4302-9367","affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]},{"raw_affiliation_string":"Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118212485","display_name":"Ahmed Karaki","orcid":"https://orcid.org/0009-0008-7762-503X","observed_orcids":["https://orcid.org/0009-0008-7762-503X"]},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Ahmed Karaki","raw_affiliation_strings":["College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar","Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha, Qatar"],"raw_orcid":"https://orcid.org/0009-0008-7762-503X","affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]},{"raw_affiliation_string":"Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056037710","display_name":"Serta\u00e7 Bayhan","orcid":"https://orcid.org/0000-0003-2027-532X","observed_orcids":["https://orcid.org/0000-0003-2027-532X"]},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]},{"id":"https://openalex.org/I95634034","display_name":"Gazi University","ror":"https://ror.org/054xkpr46","country_code":"TR","type":"education","lineage":["https://openalex.org/I95634034"]}],"countries":["QA","TR"],"is_corresponding":false,"raw_author_name":"Sertac Bayhan","raw_affiliation_strings":["Department of Electrical-Electronic Engineering, Technology Faculty, Gazi University, Ankara, Turkiye","Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0003-2027-532X","affiliations":[{"raw_affiliation_string":"Department of Electrical-Electronic Engineering, Technology Faculty, Gazi University, Ankara, Turkiye","institution_ids":["https://openalex.org/I95634034"]},{"raw_affiliation_string":"Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010833171","display_name":"Haitham Abu\u2010Rub","orcid":"https://orcid.org/0000-0001-8687-3942","observed_orcids":["https://orcid.org/0000-0001-8687-3942"]},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Haitham Abu-Rub","raw_affiliation_strings":["College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0001-8687-3942","affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081349580"],"corresponding_institution_ids":["https://openalex.org/I4210144839"],"apc_list":{"value":3560,"currency":"USD","value_usd":3560},"apc_paid":{"value":3560,"currency":"USD","value_usd":3560},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"181","issue":null,"first_page":"124158","last_page":"124158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10663","display_name":"Battery Modeling and Management","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":"Battery Modeling and Management","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":0.0,"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":0.0,"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/battery-prognostics","display_name":"battery prognostics","score":0.9900000095367432},{"id":"https://openalex.org/keywords/state-of-health-estimation","display_name":"state of health estimation","score":0.7519999742507935},{"id":"https://openalex.org/keywords/remaining-useful-life-prediction","display_name":"remaining useful life prediction","score":0.9369999766349792},{"id":"https://openalex.org/keywords/lithium-ion-batteries","display_name":"lithium-ion batteries","score":0.7829999923706055},{"id":"https://openalex.org/keywords/exponential-decay-model","display_name":"exponential decay model","score":0.6309999823570251},{"id":"https://openalex.org/keywords/battery-management-systems","display_name":"battery management systems","score":0.7829999923706055},{"id":"https://openalex.org/keywords/stacking-ensemble","display_name":"stacking ensemble","score":0.875}],"concepts":[{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.7411999702453613},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5981000065803528},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5450000166893005},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5303999781608582},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4643999934196472},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45419999957084656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4300999939441681},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4207000136375427},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.367900013923645},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.34700000286102295},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33660000562667847},{"id":"https://openalex.org/C103402496","wikidata":"https://www.wikidata.org/wiki/Q1106171","display_name":"Prediction interval","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32330000400543213},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31779998540878296},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.31279999017715454},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.29829999804496765},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.27129998803138733},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.25270000100135803},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C60316415","wikidata":"https://www.wikidata.org/wiki/Q6664520","display_name":"Local regression","level":4,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.est.2026.124158","doi":"https://doi.org/10.1016/j.est.2026.124158","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.est.2026.124158","pdf_url":null,"source":{"id":"https://openalex.org/S2764865925","display_name":"Journal of Energy Storage","issn_l":"2352-152X","issn":["2352-152X","2352-1538"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-2","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Energy Storage","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.est.2026.124158","doi":"https://doi.org/10.1016/j.est.2026.124158","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.est.2026.124158","pdf_url":null,"source":{"id":"https://openalex.org/S2764865925","display_name":"Journal of Energy Storage","issn_l":"2352-152X","issn":["2352-152X","2352-1538"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-2","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Energy Storage","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.75},{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5378999710083008}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334468","display_name":"Qatar National Library","ror":"https://ror.org/02jv93662"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W39129164","https://openalex.org/W1498436455","https://openalex.org/W1502922572","https://openalex.org/W1678356000","https://openalex.org/W1988790447","https://openalex.org/W2013679194","https://openalex.org/W2078279667","https://openalex.org/W2122825543","https://openalex.org/W2181523240","https://openalex.org/W2295598076","https://openalex.org/W2765893638","https://openalex.org/W3201108028","https://openalex.org/W4239510810","https://openalex.org/W4380368844","https://openalex.org/W4386136316","https://openalex.org/W4399975363","https://openalex.org/W4404403883","https://openalex.org/W4404584826","https://openalex.org/W4405249493","https://openalex.org/W4405934299","https://openalex.org/W4406290456","https://openalex.org/W4407562503","https://openalex.org/W4411337777","https://openalex.org/W4412701707","https://openalex.org/W4415071349","https://openalex.org/W7117727821"],"related_works":["https://openalex.org/W4362604044","https://openalex.org/W7165478204","https://openalex.org/W7115594309","https://openalex.org/W4297368531","https://openalex.org/W4200394082","https://openalex.org/W2546416483","https://openalex.org/W7166836981","https://openalex.org/W4386986738","https://openalex.org/W6983175299","https://openalex.org/W7067521454"],"abstract_inverted_index":{"Battery":[0],"management":[1],"systems":[2],"require":[3],"prognostic":[4,21],"methods":[5],"that":[6,156,192],"generalize":[7],"across":[8],"diverse":[9],"operating":[10,63,313],"conditions":[11,64],"while":[12],"remaining":[13],"computationally":[14],"efficient.":[15],"This":[16,168],"paper":[17],"presents":[18],"a":[19,34,50,75,111,127,144,162,178,188,200,216,220,225,233,246,283],"unified":[20],"framework":[22,91],"whose":[23],"regression":[24,129,139,180,226,289],"models,":[25],"once":[26,287],"trained":[27,71,293],"offline":[28,98],"on":[29,296],"multi-cycle":[30],"historical":[31],"data":[32],"from":[33,49,62,155,161],"fleet":[35],"of":[36,43,45,57,77],"batteries,":[37],"support":[38],"at":[39,166],"deployment:":[40],"(i)":[41],"prediction":[42,281],"state":[44],"health":[46],"(SOH)":[47],"trajectories":[48],"single":[51,163],"discharge":[52,59,85,148,164,261,307],"cycle,":[53],"and":[54,72,116,212,228,242,245,254,268,294],"(ii)":[55],"forecasting":[56,190,278],"full":[58,103],"voltage":[60],"curves":[61,262],"for":[65,143,304],"scenario":[66],"analysis.":[67],"The":[68,256],"approach":[69],"is":[70,108,122,170,206,249],"validated":[73],"using":[74,240],"dataset":[76],"26":[78],"Lithium-ion":[79],"(Li-ion)":[80],"packs":[81],"cycled":[82],"under":[83,263,272],"various":[84],"regimes.":[86],"For":[87,197],"SOH":[88,175,280],"forecasting,":[89,199],"the":[90,97,117,132,264,302],"operates":[92],"in":[93],"two":[94],"stages.":[95],"In":[96,131],"training":[99],"stage,":[100,136],"each":[101],"pack\u2019s":[102],"or":[104],"partial":[105],"capacity":[106],"trajectory":[107],"represented":[109],"by":[110,232],"modified":[112],"exponential":[113],"decay":[114,119],"law,":[115],"governing":[118],"parameter":[120],"\ud835\udc4f":[121,142],"extracted":[123],"via":[124],"curve-fitting":[125],"as":[126,177,224],"supervised":[128],"target.":[130],"subsequent":[133],"online":[134],"inference":[135],"this":[137],"already-trained":[138],"model":[140],"predicts":[141],"new,":[145],"previously":[146],"unseen":[147],"cycle":[149,153,165],"without":[150],"requiring":[151],"future":[152],"observations":[154],"battery,":[157],"enabling":[158],"RUL":[159],"estimation":[160],"deployment.":[167],"formulation":[169],"data-efficient":[171],"because":[172],"it":[173],"recasts":[174],"prognostics":[176,284],"low-dimensional":[179],"problem":[181],"through":[182],"parametric":[183],"curve":[184],"fitting,":[185],"rather":[186],"than":[187],"time-series":[189],"task":[191],"typically":[193],"requires":[194],"multiple":[195],"cycles.":[196],"discharge-curve":[198,277],"constrained":[201],"tri-regional":[202],"cubic":[203],"Hermite":[204],"parameterization":[205],"employed":[207],"to":[208,251],"capture":[209],"open-circuit":[210],"potential":[211],"loading":[213],"conditions,":[214],"with":[215,279],"fixed":[217],"early-time":[218],"knot,":[219],"cycle-specific":[221],"knot":[222],"predicted":[223],"target,":[227],"an":[229],"end-time":[230],"determined":[231],"cutoff-voltage":[234],"event.":[235],"Regression":[236],"models":[237,258,290],"are":[238],"assessed":[239],"cross-validation":[241],"Pareto-based":[243],"selection,":[244],"stacking":[247],"ensemble":[248],"used":[250],"enhance":[252],"robustness":[253],"generalization.":[255],"resulting":[257],"generate":[259],"consistent":[260],"evaluated":[265],"constant-current":[266],"profiles":[267],"enable":[269],"what-if":[270],"studies":[271],"candidate":[273,312],"operational":[274],"profiles.":[275],"Integrating":[276],"yields":[282],"workflow":[285],"that,":[286],"its":[288],"have":[291],"been":[292],"calibrated":[295],"experimental":[297],"cycling":[298],"data,":[299],"can":[300],"reduce":[301],"need":[303],"additional":[305],"physical":[306],"experiments":[308],"when":[309],"evaluating":[310],"new":[311],"conditions.":[314]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-09-01T00:00:00"}