{"id":"https://openalex.org/W4361984398","doi":"https://doi.org/10.1109/access.2023.3263588","title":"Design and Fault Diagnosis of Induction Motor Using ML-Based Algorithms for EV Application","display_name":"Design and Fault Diagnosis of Induction Motor Using ML-Based Algorithms for EV Application","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4361984398","doi":"https://doi.org/10.1109/access.2023.3263588"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3263588","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3263588","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10089411.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10089411.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085820607","display_name":"M Aishwarya","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"M. Aishwarya","raw_affiliation_strings":["School of Electrical Engineering, Vellore Institute of Technology (VIT), Vellore, India"],"raw_orcid":"https://orcid.org/0009-0001-9776-4693","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Vellore Institute of Technology (VIT), Vellore, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053718918","display_name":"R. M. Brisilla","orcid":"https://orcid.org/0000-0003-1387-0585"},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. M. Brisilla","raw_affiliation_strings":["School of Electrical Engineering, Vellore Institute of Technology (VIT), Vellore, India"],"raw_orcid":"https://orcid.org/0000-0003-1387-0585","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Vellore Institute of Technology (VIT), Vellore, India","institution_ids":["https://openalex.org/I876193797"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085820607"],"corresponding_institution_ids":["https://openalex.org/I876193797"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.902,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.97528237,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"11","issue":null,"first_page":"34186","last_page":"34197"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9973000288009644,"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"}},"topics":[{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9973000288009644,"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"}},{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.9908000230789185,"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/T10504","display_name":"Sensorless Control of Electric Motors","score":0.9829999804496765,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6655687093734741},{"id":"https://openalex.org/keywords/induction-motor","display_name":"Induction motor","score":0.6445791125297546},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6062462329864502},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.599755048751831},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5741028785705566},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5359632968902588},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5355797410011292},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5307248830795288},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48103195428848267},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.4711885452270508},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46818530559539795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43173742294311523},{"id":"https://openalex.org/keywords/torque","display_name":"Torque","score":0.4206133186817169},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.33731013536453247},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.2078460156917572},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17768555879592896},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14882275462150574},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1093464195728302}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6655687093734741},{"id":"https://openalex.org/C80962145","wikidata":"https://www.wikidata.org/wiki/Q207450","display_name":"Induction motor","level":3,"score":0.6445791125297546},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6062462329864502},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.599755048751831},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5741028785705566},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5359632968902588},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5355797410011292},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5307248830795288},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48103195428848267},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.4711885452270508},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46818530559539795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43173742294311523},{"id":"https://openalex.org/C144171764","wikidata":"https://www.wikidata.org/wiki/Q48103","display_name":"Torque","level":2,"score":0.4206133186817169},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.33731013536453247},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.2078460156917572},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17768555879592896},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14882275462150574},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1093464195728302},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","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/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3263588","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3263588","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10089411.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e26257fd31164b88b2d4fe670f58227e","is_oa":true,"landing_page_url":"https://doaj.org/article/e26257fd31164b88b2d4fe670f58227e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 34186-34197 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3263588","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3263588","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10089411.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4361984398.pdf","grobid_xml":"https://content.openalex.org/works/W4361984398.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W3219797","https://openalex.org/W54963364","https://openalex.org/W1976431019","https://openalex.org/W2010159163","https://openalex.org/W2017528957","https://openalex.org/W2034061890","https://openalex.org/W2056799078","https://openalex.org/W2106715603","https://openalex.org/W2112312998","https://openalex.org/W2132071458","https://openalex.org/W2155589344","https://openalex.org/W2164111100","https://openalex.org/W2164586954","https://openalex.org/W2338539395","https://openalex.org/W2421935951","https://openalex.org/W2541280515","https://openalex.org/W2559999082","https://openalex.org/W2583644357","https://openalex.org/W2589145330","https://openalex.org/W2744790985","https://openalex.org/W2766373668","https://openalex.org/W2780347156","https://openalex.org/W2890593097","https://openalex.org/W2895902335","https://openalex.org/W2913289332","https://openalex.org/W2946493557","https://openalex.org/W2956467153","https://openalex.org/W2966507006","https://openalex.org/W2975655940","https://openalex.org/W2979499097","https://openalex.org/W3004464175","https://openalex.org/W3007901506","https://openalex.org/W3040676687","https://openalex.org/W3049107215","https://openalex.org/W3094627074","https://openalex.org/W3103109707","https://openalex.org/W3170591781","https://openalex.org/W3176870635","https://openalex.org/W3187554634","https://openalex.org/W3206609282","https://openalex.org/W4206646822","https://openalex.org/W4294796072"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W2885516856","https://openalex.org/W4289703016","https://openalex.org/W4310224730","https://openalex.org/W1985505753"],"abstract_inverted_index":{"The":[0,92],"need":[1],"for":[2,98,152,174,182],"alternate":[3],"transportation":[4],"is":[5,80,96,115],"driven":[6],"by":[7],"the":[8,14,24,43,49,72,85,184],"increased":[9],"fossil":[10,37],"fuel":[11],"cost":[12],"and":[13,33,68,101,148,155,165,187],"adverse":[15],"effects":[16],"of":[17,45,51,74],"climatic":[18],"change.":[19],"Electric":[20],"vehicles":[21],"(EVs)":[22],"are":[23,169,189],"best":[25],"option":[26],"as":[27,171],"they":[28],"have":[29],"less":[30],"carbon":[31],"footprint":[32],"reduced":[34],"dependency":[35],"on":[36],"fuels.":[38],"Prodigious":[39],"efforts":[40],"to":[41,81],"enhance":[42],"efficiency":[44],"EVs":[46],"resulted":[47],"in":[48,58,84],"development":[50],"highly":[52,60],"efficient":[53,61],"three-phase":[54],"induction":[55,62],"motors.":[56],"Difficulties":[57],"designing":[59],"motors":[63],"(IM)":[64],"with":[65,118,179],"high":[66],"torque":[67],"power":[69,104],"factors":[70],"hindered":[71],"success":[73],"EV":[75,94],"applications.":[76],"Hence,":[77],"our":[78],"aim":[79],"diagnosis":[82],"fault":[83,112],"designed":[86,97],"IM":[87],"under":[88],"variable":[89,180],"load":[90,181],"conditions.":[91,157],"proposed":[93],"motor":[95],"415V,":[99],"50Hz,":[100],"5HP":[102],"output":[103],"rating":[105],"using":[106],"ANSYS":[107],"RMxprt":[108],"simulation":[109],"software.":[110],"A":[111],"detection":[113],"strategy":[114],"also":[116],"implemented":[117],"various":[119],"machine":[120,192],"learning":[121],"(ML)":[122],"techniques":[123],"like":[124],"Support":[125],"Vector":[126],"Machine":[127],"(SVM),":[128],"K-nearest":[129],"neighbors":[130],"(k-NN),":[131],"ML":[132],"perceptron":[133],"(MLP),":[134],"Random":[135],"Forest":[136],"(RF),":[137],"Decision":[138],"Tree":[139],"(DT),":[140],"Gradient":[141,145],"boosting":[142],"(GB),":[143],"Extreme":[144],"Boosting":[146],"(XGBoost),":[147],"Deep":[149],"Learning":[150],"(DL)":[151],"both":[153],"healthy":[154,186],"faulty":[156,172,188],"Short":[158],"Circuit":[159],"(SC),":[160],"High":[161],"Resistance":[162],"connection":[163],"(HRC),":[164],"Open-Phase":[166],"circuit":[167],"(OPC)":[168],"considered":[170],"states":[173,185],"this":[175],"study.":[176],"Motor":[177],"performance":[178],"all":[183],"evaluated":[190],"through":[191],"learning.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}