Effect of outside temperature on energy consumption of electric vehicles: Real-time big data and artificial intelligence-aided seahorse optimization approach

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dc.contributor.authorEkici, Yunus Emre
dc.contributor.authorKaradag, Teoman
dc.contributor.authorAkdag, Ozan
dc.contributor.authorAydin, Ahmet Arif
dc.date.accessioned2026-04-04T13:32:57Z
dc.date.available2026-04-04T13:32:57Z
dc.date.issued2025
dc.departmentİnönü Üniversitesi
dc.description.abstractIn calculating the energy consumption of electric vehicles (EVs); it is very important to optimize the consumption efficiency and driving range by considering the outdoor temperature. Studies have shown that very low and very high temperatures reduce engine efficiency and significantly increase energy consumption, while affecting regenerative energy recovery. Therefore, in the presented study, the effects of outdoor temperature on range and energy consumption were investigated using real-time big data obtained from Electric Buses (EO). The field application of the study was carried out with 22 24.7-meter EOs. The EO route was divided into 4 different regions and the energy consumption for each region and the analysis of the outdoor temperature corresponding to this consumption were obtained using regression techniques. First, the energy consumption model was created and the driving cycle was calculated for each region. Then, the driving cycle for the entire route was created and the energy consumption on the route was expressed as a mathematical model. Trilayered Neural Network (TNN) gave the best result in the calculations of the entire route. Finally, the mathematical model obtained as a result of TNN was reconsidered using the SeaHorse optimization method. Considering the analysis for the entire route (R), it was calculated that the most efficient consumption is 3.02 kWh/km and this consumption value can be achieved with a temperature of 21.5oC. This study has become a reference study for other electric vehicle manufacturers in determining the range of their vehicles in different climate conditions.
dc.identifier.doi10.17341/gazimmfd.1623529
dc.identifier.issn1300-1884
dc.identifier.issn1304-4915
dc.identifier.issue4
dc.identifier.scopus2-s2.0-105025820644
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.17341/gazimmfd.1623529
dc.identifier.urihttps://hdl.handle.net/11616/108834
dc.identifier.volume40
dc.identifier.wosWOS:001668973600010
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherGazi Univ, Fac Engineering Architecture
dc.relation.ispartofJournal of the Faculty of Engineering and Architecture of Gazi University
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250329
dc.subjectElectric Vehicles
dc.subjectEnergy Consumption
dc.subjectArtificial Intelligence
dc.subjectBig Data
dc.subjectOptimization
dc.titleEffect of outside temperature on energy consumption of electric vehicles: Real-time big data and artificial intelligence-aided seahorse optimization approach
dc.typeArticle

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