Energy Uncertainty Analysis of Electric Buses

Show simple item record Vepsäläinen, Jari Ritari, Antti Lajunen, Antti Kivekäs, Klaus Tammi, Kari 2019-01-31T10:16:02Z 2019-01-31T10:16:02Z 2018-12
dc.identifier.citation Vepsäläinen , J , Ritari , A , Lajunen , A , Kivekäs , K & Tammi , K 2018 , ' Energy Uncertainty Analysis of Electric Buses ' , Energies , vol. 11 , no. 12 , 3267 .
dc.identifier.other PURE: 121927081
dc.identifier.other PURE UUID: 8bd3dbcf-fcfa-4fe5-87b1-62bed194fba2
dc.identifier.other WOS: 000455358300028
dc.identifier.other Scopus: 85058527342
dc.identifier.other Bibtex: urn:14d336588ea76f95967ed3d02e14ef15
dc.identifier.other ORCID: /0000-0002-2175-7833/work/53517816
dc.description.abstract Uncertainty in operation factors, such as the weather and driving behavior, makes it difficult to accurately predict the energy consumption of electric buses. As the consumption varies, the dimensioning of the battery capacity and charging systems is challenging and requires a dedicated decision-making process. To investigate the impact of uncertainty, six electric buses were measured in three routes with an Internet of Things (IoT) system from February 2016 to December 2017 in southern Finland in real operation conditions. The measurement results were thoroughly analyzed and the operation factors that caused variation in the energy consumption and internal resistance of the battery were studied in detail. The average energy consumption was 0.78 kWh/km and the consumption varied by more than 1 kWh/km between trips. Furthermore, consumption was 15% lower on a suburban route than on city routes. The energy consumption was mostly influenced by the ambient temperature, driving behavior, and route characteristics. The internal resistance varied mainly as a result of changes in the battery temperature and charging current. The energy consumption was predicted with above 75% accuracy with a linear model. The operation factors were correlated and a novel second-order normalization method was introduced to improve the interpretation of the results. The presented models and analyses can be integrated to powertrain and charging system design, as well as schedule planning. en
dc.format.extent 29
dc.language.iso eng
dc.relation.ispartof Energies
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject energy consumption
dc.subject electric bus
dc.subject uncertainty
dc.subject sensitivity analysis
dc.subject correlated inputs
dc.subject VEHICLES
dc.subject CONSUMPTION
dc.subject MODEL
dc.subject SYSTEM
dc.subject VALIDATION
dc.subject PREDICTION
dc.subject 1172 Environmental sciences
dc.title Energy Uncertainty Analysis of Electric Buses en
dc.type Article
dc.contributor.organization Department of Agricultural Sciences
dc.contributor.organization Agrotechnology
dc.description.reviewstatus Peer reviewed
dc.relation.issn 1996-1073
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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