{"id":"https://openalex.org/W4394709317","doi":"https://doi.org/10.48550/arxiv.2404.06125","title":"Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging","display_name":"Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging","publication_year":2024,"publication_date":"2024-04-09","ids":{"openalex":"https://openalex.org/W4394709317","doi":"https://doi.org/10.48550/arxiv.2404.06125"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2404.06125","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.06125","pdf_url":"https://arxiv.org/pdf/2404.06125","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2404.06125","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5095335167","display_name":"Sebastian Hirt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hirt, Sebastian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024375622","display_name":"Andreas H\u00f6hl","orcid":"https://orcid.org/0000-0002-2395-5446"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"H\u00f6hl, Andreas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087733086","display_name":"Joachim Schaeffer","orcid":"https://orcid.org/0000-0001-8767-4101"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schaeffer, Joachim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029388884","display_name":"Johannes Pohlodek","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pohlodek, Johannes","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083684552","display_name":"Richard D. Braatz","orcid":"https://orcid.org/0000-0003-4304-3484"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Braatz, Richard D.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5040485515","display_name":"Rolf Findeisen","orcid":"https://orcid.org/0000-0002-9112-5946"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Findeisen, Rolf","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":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.9995999932289124,"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":0.9995999932289124,"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/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9761000275611877,"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/T10808","display_name":"Electric and Hybrid Vehicle Technologies","score":0.9606999754905701,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.802935779094696},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.6806249022483826},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.6362034678459167},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5989647507667542},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.5181894898414612},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49589166045188904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33495453000068665},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2878129780292511},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.08556678891181946}],"concepts":[{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.802935779094696},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.6806249022483826},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.6362034678459167},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5989647507667542},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.5181894898414612},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49589166045188904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33495453000068665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2878129780292511},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.08556678891181946},{"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}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2404.06125","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.06125","pdf_url":"https://arxiv.org/pdf/2404.06125","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:dspace.mit.edu:1721.1/157696","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/157696","pdf_url":"https://dspace.mit.edu/bitstream/1721.1/157696/2/1-s2.0-S2405896324011947-main.pdf","source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Elsevier","raw_type":"Article"},{"id":"doi:10.48550/arxiv.2404.06125","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2404.06125","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2404.06125","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.06125","pdf_url":"https://arxiv.org/pdf/2404.06125","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4394709317.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1990079087","https://openalex.org/W2101188133","https://openalex.org/W3106461837","https://openalex.org/W3202234113","https://openalex.org/W4248731570","https://openalex.org/W2381210024","https://openalex.org/W2060165215","https://openalex.org/W3168182983","https://openalex.org/W3199608561","https://openalex.org/W4382049207"],"abstract_inverted_index":{"Tuning":[0],"parameters":[1,116,134],"in":[2],"model":[3,90,133,219],"predictive":[4],"control":[5,154,174],"(MPC)":[6],"presents":[7],"significant":[8],"challenges,":[9],"particularly":[10],"when":[11],"there":[12],"is":[13],"a":[14,152,164,215,221],"notable":[15,225],"discrepancy":[16],"between":[17],"the":[18,22,26,46,73,81,88,114,184,200],"controller's":[19],"predictions":[20],"and":[21,61,135,166,208,224],"actual":[23],"behavior":[24,162],"of":[25,49,87,131,145],"closed-loop":[27,119,143,161,195],"plant.":[28],"This":[29,149,197],"mismatch":[30],"may":[31],"stem":[32],"from":[33,91],"factors":[34],"like":[35],"substantial":[36],"model-plant":[37,227],"differences,":[38],"limited":[39],"prediction":[40,89],"horizons":[41],"that":[42,183],"do":[43],"not":[44,187],"cover":[45],"entire":[47],"time":[48],"interest,":[50],"or":[51,93,104,112],"unforeseen":[52],"system":[53],"disturbances.":[54],"Such":[55],"mismatches":[56],"can":[57],"jeopardize":[58],"both":[59],"performance":[60,120,144],"safety,":[62],"including":[63],"constraint":[64,137],"satisfaction.":[65],"Traditional":[66],"methods":[67],"address":[68],"this":[69],"issue":[70],"by":[71],"modifying":[72],"finite":[74],"horizon":[75,223],"cost":[76],"function":[77],"to":[78,117,141],"better":[79],"reflect":[80],"overall":[82],"operational":[83],"cost,":[84],"learning":[85,113,130,185],"parts":[86],"data,":[92],"implementing":[94],"robust":[95],"MPC":[96,170,218],"strategies,":[97],"which":[98],"might":[99],"be":[100],"either":[101],"computationally":[102],"intensive":[103],"overly":[105],"cautious.":[106],"As":[107],"an":[108],"alternative,":[109],"directly":[110,159],"optimizing":[111],"controller":[115],"enhance":[118],"has":[121],"been":[122],"proposed.":[123],"We":[124],"apply":[125],"Bayesian":[126,157],"optimization":[127,158],"for":[128],"efficient":[129],"unknown":[132],"parameterized":[136],"backoff":[138],"terms,":[139],"aiming":[140],"improve":[142],"battery":[146,178],"fast":[147,179],"charging.":[148],"approach":[150,186],"establishes":[151],"hierarchical":[153],"framework":[155],"where":[156],"fine-tunes":[160],"towards":[163],"global":[165],"long-term":[167],"objective,":[168],"while":[169],"handles":[171],"lower-level,":[172],"short-term":[173],"tasks.":[175],"For":[176],"lithium-ion":[177],"charging,":[180],"we":[181],"show":[182],"only":[188],"ensures":[189],"safe":[190],"operation":[191,202],"but":[192],"also":[193],"maximizes":[194],"performance.":[196],"includes":[198],"maintaining":[199],"battery's":[201],"below":[203],"its":[204],"maximum":[205],"terminal":[206],"voltage":[207],"reducing":[209],"charging":[210],"times,":[211],"all":[212],"achieved":[213],"using":[214],"standard":[216],"nominal":[217],"with":[220],"short":[222],"initial":[226],"mismatch.":[228]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}