{"id":"https://openalex.org/W4412610690","doi":"https://doi.org/10.1109/hpcc64274.2024.00220","title":"Battery Pack SOC Estimation Based on Representative Cells and Support Vector Regression","display_name":"Battery Pack SOC Estimation Based on Representative Cells and Support Vector Regression","publication_year":2024,"publication_date":"2024-12-13","ids":{"openalex":"https://openalex.org/W4412610690","doi":"https://doi.org/10.1109/hpcc64274.2024.00220"},"language":"en","primary_location":{"id":"doi:10.1109/hpcc64274.2024.00220","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcc64274.2024.00220","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on High Performance Computing and Communications (HPCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5048393106","display_name":"Yanzhong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanzhong Liu","raw_affiliation_strings":["Anhui University,School of Artificial Intelligence,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,School of Artificial Intelligence,Hefei,China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100400885","display_name":"Yuan Chen","orcid":"https://orcid.org/0000-0001-9059-3839"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Chen","raw_affiliation_strings":["Anhui University,School of Artificial Intelligence,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,School of Artificial Intelligence,Hefei,China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.5157824,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1665","last_page":"1671"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.9860000014305115,"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":0.9860000014305115,"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/T12676","display_name":"Machine Learning and ELM","score":0.0006000000284984708,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12326","display_name":"Network Packet Processing and Optimization","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5760159492492676},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5749709606170654},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5709131360054016},{"id":"https://openalex.org/keywords/battery-pack","display_name":"Battery pack","score":0.5342399477958679},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5197722315788269},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5055520534515381},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.490742564201355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26759299635887146},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24558770656585693},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2280072271823883},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22139060497283936},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15229788422584534},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.10191202163696289},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.06323805451393127}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5760159492492676},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5749709606170654},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5709131360054016},{"id":"https://openalex.org/C2778508592","wikidata":"https://www.wikidata.org/wiki/Q420116","display_name":"Battery pack","level":4,"score":0.5342399477958679},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5197722315788269},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5055520534515381},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.490742564201355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26759299635887146},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24558770656585693},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2280072271823883},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22139060497283936},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15229788422584534},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.10191202163696289},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.06323805451393127},{"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":1,"locations":[{"id":"doi:10.1109/hpcc64274.2024.00220","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcc64274.2024.00220","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on High Performance Computing and Communications (HPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2030071248","https://openalex.org/W2166364692","https://openalex.org/W2947926781","https://openalex.org/W2973471646","https://openalex.org/W3015632404","https://openalex.org/W3125582144","https://openalex.org/W3135748666","https://openalex.org/W3205033015","https://openalex.org/W4290098823","https://openalex.org/W4311214684","https://openalex.org/W4320009984","https://openalex.org/W4387331598","https://openalex.org/W4394734209","https://openalex.org/W4400934186","https://openalex.org/W4403432366","https://openalex.org/W6639343999"],"related_works":["https://openalex.org/W2769436535","https://openalex.org/W2034497065","https://openalex.org/W3089665826","https://openalex.org/W2519883542","https://openalex.org/W2735869303","https://openalex.org/W2980755701","https://openalex.org/W2912747347","https://openalex.org/W4381929093","https://openalex.org/W4295015834","https://openalex.org/W2801146782"],"abstract_inverted_index":{"To":[0],"use":[1,117],"a":[2,6,44],"battery":[3,35,45,62,69,85,106,114,159],"pack":[4,36,46,63,86,160],"in":[5,30,200],"safe":[7],"and":[8,54,74,90,93,97,103,148,151,183,197,212,217,219,224],"rational":[9],"manner,":[10],"it":[11],"is":[12,65],"crucial":[13],"to":[14,121,156,176],"exactly":[15],"predict":[16,122],"its":[17],"state":[18,111],"of":[19,33,83,100,112,209,221],"charge":[20],"(SOC).":[21],"However,":[22],"inconsistencies":[23],"between":[24],"batteries":[25],"are":[26],"inevitable,":[27],"which":[28],"results":[29,155,186],"accurate":[31],"prediction":[32],"the":[34,61,68,71,80,84,95,101,105,110,113,118,123,128,132,137,140,153,158,166,178,189],"SOC":[37,47,64,87,129,190],"remaining":[38],"challenging.":[39],"Therefore,":[40],"this":[41,77,163,201],"article":[42,78,138,164,202],"proposes":[43],"estimation":[48,191,205],"method":[49,179,192],"based":[50,193],"on":[51,194],"representative":[52,124,195],"cells":[53,125,196],"support":[55],"vector":[56],"regression":[57],"(SVR).":[58],"Firstly,":[59],"since":[60],"determined":[66],"by":[67,131],"with":[70,143,207],"minimum":[72],"rechargeable":[73,98],"dischargeable":[75,96],"capacities,":[76],"assigns":[79],"initial":[81],"values":[82],"obeying":[88],"normal":[89],"Weibull":[91],"distributions":[92],"calculates":[94],"capacities":[99],"batteries,":[102],"selects":[104],"that":[107,188],"can":[108],"represent":[109],"pack.":[115],"Secondly,":[116],"trained":[119],"SVR":[120,198],"SOC.":[126,161],"Since":[127],"predicted":[130],"model":[133],"has":[134,203],"certain":[135],"fluctuations,":[136],"uses":[139,165],"ampere-hour":[141],"integration":[142],"constraint":[144],"factor":[145],"for":[146],"smoothing":[147],"correction":[149],"processing,":[150],"employs":[152],"processed":[154],"determine":[157],"Finally,":[162],"Worldwide":[167],"Harmonized":[168],"Light":[169],"Vehicles":[170],"Test":[171],"Cycle":[172],"(WLTC)":[173],"working":[174],"condition":[175],"validate":[177],"at":[180,214],"-15\u00b0C,":[181,215],"25\u00b0C,":[182,216],"45\u00b0C.":[184],"The":[185],"show":[187],"proposed":[199],"high":[204],"accuracy,":[206],"RMSE":[208],"0.398%,":[210],"0.151%,":[211],"0.195%":[213],"45\u00b0C,":[218],"MAE":[220],"0.335%,":[222],"0.111%,":[223],"0.156%,":[225],"respectively.":[226]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}