{"id":"https://openalex.org/W7001985356","doi":null,"title":"Lithium-ion Battery Prognosis with Variational Hybrid Physics-informed Neural Networks","display_name":"Lithium-ion Battery Prognosis with Variational Hybrid Physics-informed Neural Networks","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W7001985356"},"language":"en","primary_location":{"id":"pmh:oai:stars.library.ucf.edu:etd2020-2010","doi":null,"is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/etd2020/1011","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","vabb-shw"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electronic Theses and Dissertations, 2020-2023","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://stars.library.ucf.edu/etd2020/1011","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Giorgiani do Nascimento, Renato","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Giorgiani do Nascimento, Renato","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24934133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"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/lithium-ion-batteries","display_name":"lithium-ion batteries","score":0.8980000019073486},{"id":"https://openalex.org/keywords/battery-prognostics","display_name":"battery prognostics","score":0.7129999995231628},{"id":"https://openalex.org/keywords/remaining-useful-life-prediction","display_name":"remaining useful life prediction","score":0.902999997138977},{"id":"https://openalex.org/keywords/physics-informed-neural-networks","display_name":"physics-informed neural networks","score":0.8849999904632568},{"id":"https://openalex.org/keywords/variational-bayesian-inference","display_name":"variational inference","score":0.8600000143051147},{"id":"https://openalex.org/keywords/hybrid-physics-data-driven-modeling","display_name":"hybrid physics-data models","score":0.7409999966621399},{"id":"https://openalex.org/keywords/model-reduction","display_name":"model reduction","score":0.7390000224113464},{"id":"https://openalex.org/keywords/battery-degradation","display_name":"battery degradation","score":0.7319999933242798},{"id":"https://openalex.org/keywords/residual-capacity","display_name":"residual capacity","score":0.6930000185966492},{"id":"https://openalex.org/keywords/state-of-charge-estimation","display_name":"state of charge estimation","score":0.7609999775886536},{"id":"https://openalex.org/keywords/bayesian-fusion","display_name":"Bayesian fusion","score":0.5590000152587891},{"id":"https://openalex.org/keywords/censored-data","display_name":"censored data","score":0.9150000214576721},{"id":"https://openalex.org/keywords/battery-health-management","display_name":"battery health management","score":0.6140000224113464}],"concepts":[{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.7096999883651733},{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.6901000142097473},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5529999732971191},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5503000020980835},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5331000089645386},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.42010000348091125},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4052000045776367},{"id":"https://openalex.org/C2989104859","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery capacity","level":4,"score":0.38589999079704285},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.38199999928474426},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3686000108718872},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.3418999910354614},{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.3312999904155731},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.32420000433921814},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3050000071525574},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.28220000863075256},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C2779136927","wikidata":"https://www.wikidata.org/wiki/Q900762","display_name":"Electric-vehicle battery","level":4,"score":0.26080000400543213},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.25839999318122864},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.2542000114917755},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.2524000108242035},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:stars.library.ucf.edu:etd2020-2010","doi":null,"is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/etd2020/1011","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","vabb-shw"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electronic Theses and Dissertations, 2020-2023","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:stars.library.ucf.edu:etd2020-2010","doi":null,"is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/etd2020/1011","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","vabb-shw"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electronic Theses and Dissertations, 2020-2023","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8485000133514404}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4317597308","https://openalex.org/W4386136316","https://openalex.org/W3201108028","https://openalex.org/W3186940052","https://openalex.org/W7049248887","https://openalex.org/W4415747929","https://openalex.org/W4388116052","https://openalex.org/W3215912487","https://openalex.org/W4403022149","https://openalex.org/W4388522651"],"abstract_inverted_index":{"Lithium-ion":[0],"batteries":[1,189],"are":[2,47,266],"an":[3],"increasingly":[4],"popular":[5],"source":[6],"of":[7,21,104,109,149,206,223,271],"power":[8],"for":[9,88,125],"many":[10],"electric":[11,16],"applications.":[12,93],"Applications":[13],"range":[14],"from":[15,115],"cars,":[17],"driven":[18],"by":[19,54],"thousands":[20],"people":[22],"every":[23],"day,":[24],"to":[25,49,72,202,216,262],"existing":[26],"and":[27,37,59,90,100,117,129,166,170],"future":[28,283],"air":[29,39],"vehicles,":[30],"such":[31],"as":[32],"unmanned":[33],"aircraft":[34],"vehicles":[35],"(UAVs)":[36],"urban":[38],"mobility":[40],"(UAM)":[41],"drones.":[42],"Therefore,":[43],"robust":[44],"modeling":[45],"approaches":[46],"essential":[48],"ensure":[50],"high":[51],"reliability":[52],"levels":[53],"monitoring":[55],"battery":[56,78,110,127,231,251,291],"state-of-charge":[57],"(SOC)":[58],"forecasting":[60],"the":[61,73,102,106,150,162,175,203,207,221,230,263,272,281],"remaining":[62],"useful":[63],"life":[64],"(RUL).":[65],"Building":[66],"principled-based":[67],"models":[68,85,96,135,146],"is":[69,233,248,294],"challenging":[70],"due":[71],"complex":[74],"electrochemistry":[75],"that":[76,132],"governs":[77],"operation,":[79],"which":[80,182],"would":[81],"entail":[82],"computationally":[83],"expensive":[84],"not":[86],"suited":[87],"prognosis":[89],"health":[91],"management":[92],"Alternatively,":[94],"reduced-order":[95,145],"can":[97,278],"be":[98],"used":[99],"have":[101],"advantage":[103],"capturing":[105],"overall":[107],"behavior":[108],"discharge,":[111],"although":[112],"they":[113],"suffer":[114],"simplifications":[116],"residual":[118,204,284],"discrepancy.":[119],"We":[120,168],"propose":[121],"a":[122,192,213],"hybrid":[123,196,264,273],"solution":[124],"Li-ion":[126,188],"discharge":[128,152,185,227],"aging":[130,199],"prediction":[131],"directly":[133],"implements":[134],"based":[136],"on":[137,187],"first-principle":[138],"within":[139],"modern":[140],"recurrent":[141],"neural":[142,276],"networks.":[143],"While":[144],"describe":[147],"part":[148],"voltage":[151],"under":[153],"constant":[154],"or":[155,238],"variable":[156],"loading":[157],"conditions,":[158],"data-driven":[159],"kernels":[160],"reduce":[161],"gap":[163],"between":[164],"predictions":[165],"observations.":[167],"developed":[169],"validated":[171],"our":[172,255],"approach":[173,215,257],"using":[174],"NASA":[176],"Prognostics":[177],"Data":[178],"Repository":[179],"Battery":[180],"dataset,":[181],"contains":[183],"experimental":[184],"data":[186,219],"obtained":[190],"in":[191,220,287],"controlled":[193],"environment.":[194],"Our":[195,268],"model":[197,265],"tracks":[198],"parameters":[200],"connected":[201],"capacity":[205,232],"battery.":[208],"In":[209],"addition,":[210],"we":[211],"use":[212],"Bayesian":[214,269],"merge":[217],"fleet-wide":[218],"form":[222],"priors":[224],"with":[225],"battery-specific":[226],"cycles,":[228],"where":[229,289],"fully":[234],"available":[235,241],"(complete":[236],"data)":[237],"only":[239],"partially":[240],"(censored":[242],"data).":[243],"The":[244],"model's":[245],"predictive":[246],"capability":[247],"monitored":[249],"throughout":[250],"usage.":[252],"This":[253],"way,":[254],"proposed":[256],"indicates":[258],"when":[259],"significant":[260],"updates":[261],"needed.":[267],"implementation":[270],"variational":[274],"physics-informed":[275],"network":[277],"reliably":[279],"predict":[280],"battery's":[282],"capacity,":[285],"even":[286],"cases":[288],"previous":[290],"usage":[292],"history":[293],"unknown.":[295]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2025-10-10T00:00:00"}