{"id":"https://openalex.org/W4400646887","doi":"https://doi.org/10.1109/iv55156.2024.10588445","title":"Enhancing Electric Vehicle Energy Consumption Prediction: Integrating Elevation into Machine Learning Model","display_name":"Enhancing Electric Vehicle Energy Consumption Prediction: Integrating Elevation into Machine Learning Model","publication_year":2024,"publication_date":"2024-06-02","ids":{"openalex":"https://openalex.org/W4400646887","doi":"https://doi.org/10.1109/iv55156.2024.10588445"},"language":"en","primary_location":{"id":"doi:10.1109/iv55156.2024.10588445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"article","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/A5100403173","display_name":"Lin Wang","orcid":"https://orcid.org/0000-0002-5491-8840"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lin Wang","raw_affiliation_strings":["Xi&#x2019;an Telenav Software Ltd,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Telenav Software Ltd,Shaanxi,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115602237","display_name":"Yong Yang","orcid":"https://orcid.org/0000-0002-5742-1637"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong Yang","raw_affiliation_strings":["Xi&#x2019;an Telenav Software Ltd,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Telenav Software Ltd,Shaanxi,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083648335","display_name":"Kuan Zhang","orcid":"https://orcid.org/0000-0003-1014-4975"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuan Zhang","raw_affiliation_strings":["Xi&#x2019;an Telenav Software Ltd,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Telenav Software Ltd,Shaanxi,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112098260","display_name":"Yuan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan Liu","raw_affiliation_strings":["Xi&#x2019;an Telenav Software Ltd,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Telenav Software Ltd,Shaanxi,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006165246","display_name":"J. Zhu","orcid":"https://orcid.org/0000-0003-2155-2659"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinhua Zhu","raw_affiliation_strings":["Xi&#x2019;an Telenav Software Ltd,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Telenav Software Ltd,Shaanxi,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111257457","display_name":"Daping Dang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daping Dang","raw_affiliation_strings":["Xi&#x2019;an Telenav Software Ltd,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Telenav Software Ltd,Shaanxi,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100403173"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8878,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73709207,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2936","last_page":"2941"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.996399998664856,"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"}},"topics":[{"id":"https://openalex.org/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.996399998664856,"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/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9718000292778015,"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/energy-consumption","display_name":"Energy consumption","score":0.7237398624420166},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6458051800727844},{"id":"https://openalex.org/keywords/elevation","display_name":"Elevation (ballistics)","score":0.6237527132034302},{"id":"https://openalex.org/keywords/electric-vehicle","display_name":"Electric vehicle","score":0.5059220194816589},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4897904396057129},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.41735750436782837},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33571019768714905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3285568058490753},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16581380367279053},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.09382656216621399},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07160529494285583}],"concepts":[{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.7237398624420166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6458051800727844},{"id":"https://openalex.org/C37054046","wikidata":"https://www.wikidata.org/wiki/Q641888","display_name":"Elevation (ballistics)","level":2,"score":0.6237527132034302},{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.5059220194816589},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4897904396057129},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.41735750436782837},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33571019768714905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3285568058490753},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16581380367279053},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.09382656216621399},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07160529494285583},{"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/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},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv55156.2024.10588445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8899999856948853,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1502191042","https://openalex.org/W1589349916","https://openalex.org/W1956718793","https://openalex.org/W1985343312","https://openalex.org/W2016087887","https://openalex.org/W2043128936","https://openalex.org/W2110326729","https://openalex.org/W2343806141","https://openalex.org/W2528716468","https://openalex.org/W2579634931","https://openalex.org/W2584168942","https://openalex.org/W2610481170","https://openalex.org/W2615724625","https://openalex.org/W2750433864","https://openalex.org/W2808701198","https://openalex.org/W2921257412","https://openalex.org/W2955938111","https://openalex.org/W3016971498","https://openalex.org/W3021005717","https://openalex.org/W3082930479","https://openalex.org/W3098333219","https://openalex.org/W3177360131","https://openalex.org/W3182706339","https://openalex.org/W4308068717"],"related_works":["https://openalex.org/W2274139355","https://openalex.org/W4297745244","https://openalex.org/W4214628662","https://openalex.org/W2156822401","https://openalex.org/W2037518538","https://openalex.org/W3092380670","https://openalex.org/W3125847301","https://openalex.org/W4313390786","https://openalex.org/W2089393798","https://openalex.org/W2356819012"],"abstract_inverted_index":{"The":[0,56,100],"energy":[1,15,31,48,77,110],"consumed":[2],"to":[3,43,75,133,150],"overcome":[4],"gravity":[5],"during":[6],"elevation":[7,22,54,62,117],"gain":[8],"is":[9,59,73],"a":[10,66,80],"significant":[11],"factor":[12],"in":[13,94],"the":[14,27,45,95,105,114,120,126,137,144],"consumption":[16,49,111],"of":[17,29,47,70,82,108,116,125,143],"electric":[18],"vehicles":[19],"(EVs).":[20],"Assessing":[21],"influence":[23],"can":[24],"help":[25],"improve":[26,44],"accuracy":[28,46,107],"estimated":[30],"consumption,":[32],"which":[33],"will":[34],"alleviate":[35],"drivers'":[36],"range":[37],"anxiety.":[38],"This":[39],"study":[40],"explores":[41],"how":[42],"prediction":[50,106,127,145],"for":[51],"EVs":[52,109],"using":[53],"features.":[55],"trip":[57,84],"dataset":[58],"supplemented":[60],"with":[61,113],"features,":[63,118],"and":[64,90,136],"then":[65],"voting":[67],"ensemble":[68],"model":[69],"machine":[71],"learning":[72],"proposed":[74],"predict":[76],"consumption.":[78],"Also,":[79],"total":[81],"10,847":[83],"records":[85],"from":[86,130],"16":[87],"hilliness":[88],"cities":[89,93],"13":[91],"flatness":[92],"United":[96],"States":[97],"are":[98],"studied.":[99],"experimental":[101],"results":[102],"show":[103],"that":[104],"improves":[112],"inclusion":[115],"where":[119],"Mean":[121],"Absolute":[122],"Error":[123],"(MAE)":[124],"result":[128,146],"decreases":[129],"796":[131],"Wh":[132],"695":[134],"Wh,":[135],"R-squared":[138],"(R<sup":[139],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[140],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>)":[141],"score":[142],"increases":[147],"by":[148],"1.6%":[149],"finally":[151],"reach":[152],"94.4%.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}