{"id":"https://openalex.org/W2981310561","doi":"https://doi.org/10.23919/iconac.2019.8895072","title":"Heavy duty vehicle fuel consumption modeling using artificial neural networks","display_name":"Heavy duty vehicle fuel consumption modeling using artificial neural networks","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2981310561","doi":"https://doi.org/10.23919/iconac.2019.8895072","mag":"2981310561"},"language":"en","primary_location":{"id":"doi:10.23919/iconac.2019.8895072","is_oa":false,"landing_page_url":"https://doi.org/10.23919/iconac.2019.8895072","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 25th International Conference on Automation and Computing (ICAC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://dora.dmu.ac.uk/handle/2086/18521","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082922366","display_name":"Oskar Wysocki","orcid":"https://orcid.org/0000-0002-7053-4919"},"institutions":[{"id":"https://openalex.org/I169333911","display_name":"Gda\u0144sk University of Technology","ror":"https://ror.org/006x4sc24","country_code":"PL","type":"education","lineage":["https://openalex.org/I169333911"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Oskar Wysocki","raw_affiliation_strings":["Department of Energy and Industrial Apparatus, Gda\u0144sk University of Technology, Gda\u0144sk, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Energy and Industrial Apparatus, Gda\u0144sk University of Technology, Gda\u0144sk, Poland","institution_ids":["https://openalex.org/I169333911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056865979","display_name":"Lipika Deka","orcid":"https://orcid.org/0000-0001-8986-884X"},"institutions":[{"id":"https://openalex.org/I66943878","display_name":"De Montfort University","ror":"https://ror.org/0312pnr83","country_code":"GB","type":"education","lineage":["https://openalex.org/I66943878"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lipika Deka","raw_affiliation_strings":["Department of Computer Science and Informatics, De Montfort University, Leicester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Informatics, De Montfort University, Leicester, UK","institution_ids":["https://openalex.org/I66943878"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055283205","display_name":"David Elizondo","orcid":"https://orcid.org/0000-0002-7398-5870"},"institutions":[{"id":"https://openalex.org/I169333911","display_name":"Gda\u0144sk University of Technology","ror":"https://ror.org/006x4sc24","country_code":"PL","type":"education","lineage":["https://openalex.org/I169333911"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"David Elizondo","raw_affiliation_strings":["Department of Energy and Industrial Apparatus, Gda\u0144sk University of Technology, Gda\u0144sk, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Energy and Industrial Apparatus, Gda\u0144sk University of Technology, Gda\u0144sk, Poland","institution_ids":["https://openalex.org/I169333911"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8624,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71023102,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9998999834060669,"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/T12095","display_name":"Vehicle emissions and performance","score":0.9998999834060669,"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/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1507","display_name":"Fluid Flow and Transfer Processes"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13990","display_name":"Engine and Fuel Emissions","score":0.9776999950408936,"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/fuel-efficiency","display_name":"Fuel efficiency","score":0.7430636882781982},{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.707672655582428},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7065658569335938},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.6140837073326111},{"id":"https://openalex.org/keywords/driving-cycle","display_name":"Driving cycle","score":0.5799936056137085},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5550110936164856},{"id":"https://openalex.org/keywords/torque","display_name":"Torque","score":0.5525050163269043},{"id":"https://openalex.org/keywords/test-bench","display_name":"Test bench","score":0.5442564487457275},{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.4986450672149658},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49764540791511536},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.4867687225341797},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.45381420850753784},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.44504499435424805},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.4214113652706146},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.41350027918815613},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16459286212921143},{"id":"https://openalex.org/keywords/electric-vehicle","display_name":"Electric vehicle","score":0.07192918658256531},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07164254784584045}],"concepts":[{"id":"https://openalex.org/C45882903","wikidata":"https://www.wikidata.org/wiki/Q5042317","display_name":"Fuel efficiency","level":2,"score":0.7430636882781982},{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.707672655582428},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7065658569335938},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.6140837073326111},{"id":"https://openalex.org/C169042556","wikidata":"https://www.wikidata.org/wiki/Q16246150","display_name":"Driving cycle","level":4,"score":0.5799936056137085},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5550110936164856},{"id":"https://openalex.org/C144171764","wikidata":"https://www.wikidata.org/wiki/Q48103","display_name":"Torque","level":2,"score":0.5525050163269043},{"id":"https://openalex.org/C2776266606","wikidata":"https://www.wikidata.org/wiki/Q476482","display_name":"Test bench","level":2,"score":0.5442564487457275},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.4986450672149658},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49764540791511536},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4867687225341797},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.45381420850753784},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.44504499435424805},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4214113652706146},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.41350027918815613},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16459286212921143},{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.07192918658256531},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07164254784584045},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","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":2,"locations":[{"id":"doi:10.23919/iconac.2019.8895072","is_oa":false,"landing_page_url":"https://doi.org/10.23919/iconac.2019.8895072","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 25th International Conference on Automation and Computing (ICAC)","raw_type":"proceedings-article"},{"id":"pmh:oai:dora.dmu.ac.uk:2086/18521","is_oa":true,"landing_page_url":"https://dora.dmu.ac.uk/handle/2086/18521","pdf_url":null,"source":{"id":"https://openalex.org/S4306400394","display_name":"DMU Open Research Archive (De Montfort University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66943878","host_organization_name":"De Montfort University","host_organization_lineage":["https://openalex.org/I66943878"],"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":"","raw_type":"Conference"}],"best_oa_location":{"id":"pmh:oai:dora.dmu.ac.uk:2086/18521","is_oa":true,"landing_page_url":"https://dora.dmu.ac.uk/handle/2086/18521","pdf_url":null,"source":{"id":"https://openalex.org/S4306400394","display_name":"DMU Open Research Archive (De Montfort University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66943878","host_organization_name":"De Montfort University","host_organization_lineage":["https://openalex.org/I66943878"],"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":"","raw_type":"Conference"},"sustainable_development_goals":[{"score":0.8799999952316284,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W839178879","https://openalex.org/W928605087","https://openalex.org/W1829946914","https://openalex.org/W1976199480","https://openalex.org/W1976714002","https://openalex.org/W2064255210","https://openalex.org/W2066776366","https://openalex.org/W2081455928","https://openalex.org/W2290076963","https://openalex.org/W2315473363","https://openalex.org/W2411690914","https://openalex.org/W2500115679","https://openalex.org/W2517733236","https://openalex.org/W2569197996","https://openalex.org/W2753163958","https://openalex.org/W2765929154","https://openalex.org/W2775283290","https://openalex.org/W2787892586","https://openalex.org/W2895793322","https://openalex.org/W2896354094","https://openalex.org/W2898063197","https://openalex.org/W2996805069","https://openalex.org/W4285719527","https://openalex.org/W6771852231"],"related_works":["https://openalex.org/W584449260","https://openalex.org/W3118438776","https://openalex.org/W3023908086","https://openalex.org/W3006361955","https://openalex.org/W3161992182","https://openalex.org/W2900266557","https://openalex.org/W3113289758","https://openalex.org/W2057603251","https://openalex.org/W2808463094","https://openalex.org/W2047960132"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"an":[3],"artificial":[4],"neural":[5,116],"network":[6,117],"(ANN)":[7],"approach":[8],"to":[9,64,68,80,144],"modelling":[10],"fuel":[11,49,125,146,153],"consumption":[12,50,126,147],"of":[13,30,127,156],"heavy":[14],"duty":[15,109],"vehicles":[16,150],"is":[17,40,46,51],"presented.":[18],"The":[19,48,115,136],"proposed":[20],"method":[21,122,138],"uses":[22],"easy":[23],"accessible":[24],"data":[25],"collected":[26],"via":[27],"CAN":[28],"bus":[29],"the":[31,66,69,82,94,96,120,128],"truck.":[32],"As":[33],"a":[34,36,60,72],"benchmark":[35],"conventional":[37,121],"method,":[38],"which":[39],"based":[41],"on":[42,93],"polynomial":[43,83],"regression":[44,84],"model,":[45],"used.":[47],"measured":[52],"in":[53,78,131,142,148,159,161],"two":[54],"different":[55,90],"tests,":[56],"performed":[57],"by":[58],"using":[59,107],"unique":[61],"test":[62,75,104],"bench":[63],"apply":[65],"load":[67],"engine.":[70],"Firstly,":[71],"transient":[73,132],"state":[74],"was":[76,100,105],"performed,":[77],"order":[79,143],"evaluate":[81],"and":[85,123,165],"25":[86],"ANN":[87,98],"models":[88],"with":[89],"parameters.":[91],"Based":[92],"results,":[95],"best":[97],"model":[99,113,118,155],"chosen.":[101],"Then,":[102],"validation":[103],"conducted":[106],"real":[108],"cycle":[110],"loads":[111],"for":[112],"comparison.":[114],"outperformed":[119],"represents":[124],"engine":[129,163],"operating":[130],"states":[133],"significantly":[134],"better.":[135],"presented":[137],"can":[139],"be":[140],"applied":[141],"reduce":[145],"utility":[149],"delivering":[151],"accurate":[152],"economy":[154],"truck":[157],"engines,":[158],"particular":[160],"low":[162],"speed":[164],"torque":[166],"range.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2019-10-25T00:00:00"}
