Energy Uncertainty Analysis of Electric Buses

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http://hdl.handle.net/10138/298531

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Vepsäläinen , J , Ritari , A , Lajunen , A , Kivekäs , K & Tammi , K 2018 , ' Energy Uncertainty Analysis of Electric Buses ' , Energies , vol. 11 , no. 12 , 3267 . https://doi.org/10.3390/en11123267

Title: Energy Uncertainty Analysis of Electric Buses
Author: Vepsäläinen, Jari; Ritari, Antti; Lajunen, Antti; Kivekäs, Klaus; Tammi, Kari
Contributor: University of Helsinki, Department of Agricultural Sciences
Date: 2018-12
Language: eng
Number of pages: 29
Belongs to series: Energies
ISSN: 1996-1073
URI: http://hdl.handle.net/10138/298531
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.
Subject: energy consumption
electric bus
uncertainty
sensitivity analysis
correlated inputs
LITHIUM-ION BATTERIES
SENSITIVITY-ANALYSIS
DRIVING BEHAVIOR
VEHICLES
CONSUMPTION
MODEL
SYSTEM
ELECTRIFICATION
VALIDATION
PREDICTION
1172 Environmental sciences
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